energies

Article Battery Degradation Minimization-Oriented Hybrid Energy Storage System for Electric Vehicles

Cong Zhang 1 , Dai Wang 1,2,*, Bin Wang 1 and Fan Tong 1 1 Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA; [email protected] (C.Z.); [email protected] (B.W.); [email protected] (F.T.) 2 Tesla Inc., 3500 Deer Creek Rd, Palo Alto, CA 94304, USA * Correspondence: [email protected]



Received: 4 November 2019; Accepted: 2 January 2020; Published: 3 January 2020


Abstract: A battery/supercapacitor hybrid energy storage system is developed to mitigate the battery degradation for electric vehicles. By coordinating the battery and supercapacitor, the proposed system avoids using the large bidirectional DC/DC. Through the improved topology and two added controlled switches, the battery current can be managed flexibly. Based on the battery and supercapacitor voltage, seven operation modes of battery and capacitor cooperation are designed. The control strategy is redesigned to match the modes, in which the key control parameters are calibrated based on three standard driving cycles. During driving, the proposed system calls the predefined parameter set by the cycle recognition technique. The objective of the cycle-related control is to maximize the harvest of the braking energy and minimize battery degradation in various driving styles. Taking the battery case solely as a benchmark and the infinite supercapacitors case as the largest battery degradation mitigation scenario, the battery degradation quantification of the proposed energy storage system shows more than 80% mitigation of the maximum theoretical battery degradation mitigation on urban dynamometer driving schedule (UDDS), highway fuel economy cycle (HWFET), and high-speed (US06) driving cycle, respectively. During the tested driving cycles, the simulation result indicates the battery degradation reduced by 30% more than the battery solely scenario, which proves the benefit of the proposed system.

Keywords: electric vehicles; hybrid energy storage system; supercapacitor; battery life; electric vehicles

1. Introduction Both greenhouse gas (GHG) emission and fossil fuel consumption have been critical environment topics in recent decades. Compared to the conventional vehicle, the electric vehicle (EV) has advantages in energy consumption, exhaust emission, and average maintenance cost [1]. The lithium-ion battery is used as the supply source widely for electric vehicles [2], including the plug-in hybrid electric vehicles (PHEV) [3], battery electric vehicles (BEV), and fuel cell electric vehicles (FCEV) [4]. However, there are two concerns in the lithium battery application, including the expensive energy capacity and the limited driving environment, which limits the promotion of electric cars. Mitigating the battery capacity degradation and prolonging the battery life are two key goals in the battery energy management system [5]. During the vehicle configuration, the energy storage system is required to meet both the power and energy demand. For the lithium-ion battery, the power density is relatively lower than energy density. However, the capacitor is just the opposite. In the energy storage system (ESS) configuration, the charging mileage requirement should be met firstly [6]. Considering the power density features, the power configuration is not high enough. As a result, the battery suffers high discharging current, which accelerates the capacity degradation rate; that is to say, the strong discharge current accelerates

Energies 2020, 13, 246; doi:10.3390/en13010246 www.mdpi.com/journal/energies Energies 2020, 13, 246 2 of 21 the degradation [7]. Furthermore, frequent charging and discharging are harmful to battery life [8,9]. In some extreme driving situations, the battery may be overcharged and discharged, which reduces the battery lifecycle seriously [10,11]. To solve the problem, the supercapacitor (SC) is usually configured to assist the peak power demand [12]. Moreover, increasing the battery size is another method to enhance the power demand of ESS. However, this method leads to high configuration costs. Further, with the battery size raising, the balancing difficulty among battery cells increases exponentially [13]. Using the SC can avoid the above issues in the ESS design. Also, in terms of maximizing energy efficiency, it is crucial to make good use of the harvested braking energy. As the power source, the SC can supply higher power. Adding the supercapacitor to the energy storage system, the frequent discharging and charging flow across the battery can be avoided [14,15]. The literature describes the advantages of the hybrid energy storage system (HESS) [16]. First, the supercapacitor can be used to protect the lithium-ion battery from the peak-power discharging. Secondly, because the SC has a higher energy efficiency than that of battery, including the SC can improve efficiency and reduce energy loss. Thirdly, the supercapacitor can work in a wider temperature range. Finally, since the supercapacitor can absorb the braking energy, the equipped battery can skip the frequent charging operations during braking situations [17]. For the purpose of improving the above issues, multi-new hybrid energy storage system has been proposed [18–32], including the novel HESS topology and the control strategy. In the previous proposed HESS topologies, there were three main types [18]: Passive, semi-active, and fully active, which will be introduced in the following section. The passive topology is simple, there are no requirements for control or expensive power electronic converters. However, during the power source working process, the voltage of SC is same as the voltage of battery. Therefore, the SC cannot charge/discharge at peak power rate. The major problem with this topology is that it cannot effectively utilize the UC stored energy [19]. In contrast, the fully active topology is the most complicated, which adopts two bi-directional DC/DC converters [20]. It has a good effect but the most expensive cost. As for the semi-active topology, it can provide a good trade-off between the passive topology and fully topologies. At present, the semi-active topology is the HESS research hotspot. In order to minimize the cost of HESS, Jose et al. came up with an interleaved controlled bidirectional converter topology to reduce the size of traditional DC/DC converter and extend the battery lifespan [21]. Ziyou et al. adopted the unidirectional DC/DC converter to optimal the system cost and quantify battery capacity loss by adding an additional diode. In this improved case, the unidirectional DC/DC converter size can be configured to a smaller size [14]. Odeim et al. studied the energy management algorithm with the genetic strategy and investigated the power load between the battery and supercapacitor with the optimization of multi-objective [22]. Cao et al. used a new HESS topology to optimize the system cost, however, the efficiency of braking energy regenerating is not high [20]. Song et al. researched the temperature and battery influence on the optimized HESS; the simulation shows that the HESS configuration and energy management system is robust to the temperature variations and battery price [23]. According to the state of charge (SOC) of the supercapacitor, the core point is to set the changeable battery discharge power limitation in their method. Because of the HESS topology, to configure a large DC/DC converter is unavoidable [24]. According to the previous literature, the full functioning of battery/SC topology and the DC/DC cost are expensive and complicated [14,20]. For example, the bi-directional DC/DC converter has a better function, but it is more expensive than the unidirectional type [25]. Besides the HESS topology, another important issue in HESS is the control strategy. The purpose of the control strategy is to regulate the best power flows sharing to prolong the battery lifetime. There are two control routes depicted in the literature [26], rule-based approach [27] and optimization-based approach [28,29]. In order to improve the regenerative braking energy, Naseri et al. improved an improved regenerative braking system. The PI controller is used to adjust the braking torque by regulating the duty-cycle of the PWM algorithm. The features of the improved regenerative braking system can achieve constant torque regenerative braking for realizing comfort and security Energies 2020, 13, 246 3 of 21

Energies 2020, 13, x FOR PEER REVIEW 3 of 21 purposes [30]. Maciej et al. used the genetic algorithm strategy to optimize the fully active HESS decrease the battery degradation and extend the battery lifespan. Since the minimum number of system to decrease the battery degradation and extend the battery lifespan. Since the minimum DC/DC converters is two in the HESS, the whole system cost is still high [31]. Nassim et al. researched number of DC/DC converters is two in the HESS, the whole system cost is still high [31]. Nassim et al. the new control strategy of HESS by reducing the battery power current to reduce battery decay. researched the new control strategy of HESS by reducing the battery power current to reduce battery Santucci et al. have proposed to organize the energy management of a three sources hybrid electric vehicle in decay. Santucci et al. have proposed to organize the energy management of a three sources hybrid two-level. The first level was managed by an optimization-based control strategy while the second level can be electric vehicle in two-level. The first level was managed by an optimization-based control strategy managed by a rule-based or an optimization-based EMS [32]. Wang et al. have proposed a real-time while the second level can be managed by a rule-based or an optimization-based EMS [32]. Wang et al. optimization-based control strategy for a battery–SCs HESS using a single DC/DC converter. have proposed a real-time optimization-based control strategy for a battery–SCs HESS using a single Validation on a standard urban driving cycle ECE-15 considered known in advance has been DC/DC converter. Validation on a standard urban driving cycle ECE-15 considered known in advance performed [33]. Whatever the approach for the HESS control, the variations of the driving cycle affect has been performed [33]. Whatever the approach for the HESS control, the variations of the driving the HESS performances. Indeed, the HESS parameters are usually determined for a specific driving cycle affect the HESS performances. Indeed, the HESS parameters are usually determined for a specific cycle that represents an ideal case. driving cycle that represents an ideal case. Since the energy density of lithium-ion is much larger than the supercapacitor, the battery is Since the energy density of lithium-ion is much larger than the supercapacitor, the battery is usually regarded as the primary energy source in HESS [12]. Furthermore, the coordination between usually regarded as the primary energy source in HESS [12]. Furthermore, the coordination between battery and SC should guarantee that the HESS can harvest the regenerative braking energy at high battery and SC should guarantee that the HESS can harvest the regenerative braking energy at high efficiency. Figure 1 is a brief overview of the traditional HESS topologies. efficiency. Figure1 is a brief overview of the traditional HESS topologies.

(a)

(b) (c)

FigureFigure 1. 1. DifferentDifferent hybrid hybrid energy energy storage storage system system (HESS) (HESS) topologies: topologies: (a ()a passive) passive parallel parallel topology; topology; (b ()b ) battery/supercapacitorbattery/supercapacitor (SC) (SC) configuration; configuration; (c ()c )SC/battery SC/battery configuration. configuration.

1.1. Passive Parallel Topology 1.1. Passive Parallel Topology FigureFigure 1a1a shows thethe typical typical parallel parallel topology topology of theof the HESS. HESS. Since Since the battery the battery voltage voltage range isrange narrow is narrowcompared compared with SC with voltage, SC voltage, the SC the cannot SC cannot make make good good use ofuse its of wide its wide voltage voltage range. range. Generally, Generally, the typical end of discharge battery voltage is around 80% of the nominal battery voltage (Vnominal)[34], i.e., the typical end of discharge battery voltage is around 80% of the nominal battery voltage (Vnominal) [34], the usable battery voltage is [0.8Vnominal, Vnominal]. In this topology, the SC voltage is also constrained i.e., the usable battery voltage is [0.8Vnominal, Vnominal]. In this topology, the SC voltage is also constrained byby the the same same voltage voltage range range as as the the battery. battery. The The SOCSOC ofof SC SC is is calculated calculated as as follows: follows:

1 𝐸E == 𝐶𝑉CV,2 ,(1) (1) sc 2 1CV2 2 (2) 𝑆𝑂𝐶 = 2 = V . SOC = = . (2) sc 1 2 2 2 CVmax Vmax 𝐸 is the stored energy in the supercapacitor, the unit is J. C is the capacitance of supercapacitor, the unit is F. 𝑉 is the supercapacitor voltage, Vmax is the maximum voltage of supercapacitor. 𝑆𝑂𝐶 is the supercapacitor state of charge. According to the above equations, about 64% of the total energy

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Esc is the stored energy in the supercapacitor, the unit is J. C is the capacitance of supercapacitor, the unit is F. V is the supercapacitor voltage, Vmax is the maximum voltage of supercapacitor. SOCsc is the supercapacitor state of charge. According to the above equations, about 64% of the total energy stored in SC cannot be discharged. Equally, in order to realize the same usable energy in SC, the SC size requirement will be higher in the basic passive parallel topology than other topologies that use DC/DC converter. In this topology, the advantage is the low-cost configuration. No DC/DC converter is needed in the passive parallel topology. In contrast, the disadvantage is the low utility percentage of the total stored energy in SC is the main disadvantage. The voltage of SC has to follow the battery voltage, which limits the use of large power density characteristics of the SC.

1.2. Battery/SC Topology Figure1b indicates the battery /SC topology. In this topology, the DC/DC converter connects the battery and SC. Because of the bidirectional DC/DC converter, the working voltage range of SC is much wider than that in basic passive topology. The advantage of this topology is that a wider SC voltage range is conducive to the potential charging/discharging capacity of the SC. Because of higher coulombic efficiency, this topology is helpful to improve energy efficiency when harvesting the regenerative braking energy. The disadvantage of this topology is that the SC does not have enough usable energy stored. Besides, the DC/DC converter has to be set large enough to supply higher power from the battery to the motor, which increases the system cost.

1.3. SC/Battery Topology Figure1c shows the SC /battery topology diagram. Compared with the above topology, the difference is that the SC and the battery exchange the position with each other. The advantage of this topology is that the energy flow can avoid the DC/DC converter during the majority operation when the vehicle is driving. The energy loss of the DC/DC converter is lower than other topologies. In this topology, there are four disadvantages [14,15]: (a) The DC/DC converter leads to energy loss when current flows across converter [14]; (b) the frequent charging actions reduce battery life [35]; (c) the DC/DC converter needs to be configured at a large size [20]; (d) The battery energy of harvesting regenerative braking energy is lower than the SC [19].

1.4. Fully Active Topology Figure2a represents the fully active topology in which two bidirectional DC /DC converters exist [20]. In this topology, the SC, battery, and inverter are isolated separately, and the available voltage of SC can get the largest range. This topology makes good use of SC and assists the battery in the largest potential. They are all the advantages of this topology. In contrast, the dominated drawback of the topology is the high cost of two bidirectional DC/DC converters.

1.5. Multi-Input Topology Figure2b shows the multi-inputs topology, in which a multi-input bidirectional DC /DC converter works equally as the two bidirectional DC/DC converters [36]. This topology has the same features as the above fully active topology. The voltage range among SC, battery, and inverter are isolated absolutely. SC can reach a wider voltage range. The main disadvantages of the multi-input topology are the complicated structure and high cost of DC/DC converter configuration. Its pros/cons are similar to the fully active topology.

1.6. Semi-Active Topology (Bidirectional DC/DC Converter) For the purpose of reducing the DC/DC converter size, Cao et al. came up with a new topology to leverage the full functionality of battery and SC, which is introduced in Figure2c [ 20]. In this topology, a controlled switch is added to control the current flow direction. There is no controller component Energies 2020, 13, 246 5 of 21 between the SC and motor load when the SC voltage is too low to transfer the energy to motor load, the battery needs to supply the energy to both the motor load and SC even at high power demand. The advantage of this topology is the battery not only works as the unique power source during the Energieslow-power 2020, 13 cases, x FOR but PEER also REVIEW assists to supply power at high-power cases. The drawback focuses5 on of the21 DC/DC converter. Since the bidirectional DC/DC converter is mandatory during the energy flowing energybetween flowing the motor between load andthe motor battery, load the and efficiency battery, of harvestingthe efficiency braking of harvesting energy is braking not high energy when theis notSC high is charged when fully.the SC is charged fully.

1.7.1.7. Semi-Active Semi-Active Topology Topology (Unidirectional (Unidirectional DC/DC DC/DC Converter) Converter) FigureFigure 2d2d shows a lower-cost topology in wh whichich the above bidirectional DC/DC DC /DC converter converter is is replacedreplaced by by thethe unidirectionalunidirectional DC DC/DC/DC converter, converter, which wh isich proposed is proposed by Song by etSong al. [ 14et]. al. In [14]. this topology,In this topology,five modes five are modes controlled are controlled to realize to the realize coordination the coordination between batterybetween and battery SC for and all SC possible for all situations.possible situations.The novelty The of thisnovelty topology of this is the topology unidirectional is the DCunidirectional/DC converter, DC/DC rather thanconverter, a bidirectional rather than DC/DC a bidirectionalconverter. The DC/DC unidirectional converter. DC The/DC unidirectional converter can DC/DC transfer converter the energy can from transfer the regenerativethe energy from braking the regenerativesystem to the braking battery system when SC to is the fully battery charged. when The SC advantage is fully charged. of this topology The advantage is that theof this unidirectional topology isDC that/DC the converter unidirectional has a lowerDC/DC cost converter than the has bidirectional a lower cost DC than/DC the converter. bidirectional The drawback DC/DC converter. is that the Thecharging drawback efficiency is that is the not charging high enough efficiency because is not of high the energy enough consumption because of the of energy the DC /consumptionDC converter. ofThis the topologyDC/DC converter. cannot realize This thetopology high ecannotfficiency real inize both the charging high efficiency and discharge in both forcharging the battery. and dischargeFurthermore, for the the battery. SC voltage Furthermore, is controlled the strictly SC voltag highere is thancontrolled the battery, strictly which higher constrains than the the battery, usable whichenergy constrains stored in the SC. usable energy stored in SC.

(a) (b)

(c) (d)

FigureFigure 2. 2. DifferentDifferent HESS HESS topologies: topologies: (a ()a )Fully Fully active active configuration; configuration; (b ()b )multiple multiple inputs inputs DC/DC; DC/DC; (c ()c ) semi-activesemi-active configuration configuration incorporatedincorporated (bidirectional);(bidirectional); (d ()d semi-active) semi-active configuration configuration incorporated incorporated with witha diode a diode (unidirectional). (unidirectional).

AlthoughAlthough these these prior prior studies studies are are relevant relevant for for the the research research questions questions addressed addressed in in the the present present study,study, there there are are several several limitations limitations of of the the prior prior studies studies that that justify justify the the need need and and broad broad impact impact of of the the presentpresent study. study. Also, Also, we we proposed proposed our our cont contributionribution to to this this paper. paper. Including: Including: 1.1. Failed Failed to to develop develop the the HESS HESS topology topology and and the the chan changeablegeable control control strategy strategy [14]. [14]. In In this this paper, paper, thethe control control strategy strategy is is developed developed based based on on the the customized customized hardware hardware topology. topology. 2.2. To To covecove the the high high effi ciencyefficiency regenerative regenerati brakingve braking energy energy harvesting harvesting and the batteryand the discharging, battery discharging,the previous the literature previous failed literat toure use failed the unidirectional to use the unidirectional DC/DC converter DC/DC in theconverter HESS topologyin the HESS [20]. topologyIn this paper, [20]. In we this improved paper, thewe HESSimproved topology the HESS by using topology the unidirectional by using the DCunidirectional/DC converter, DC/DC with converter,two switches. with two switches. 3. Failed to improve the rule-based control strategy according to the driving cycles. In this research, the control threshold can be customized to mitigate battery degradation at various driving cycles [14,15]. 4. Failed to investigate the combination among the HESS size configuration, topology, and the control strategy. In our research, we integrated them together, and presented the quantitative battery degradation is given across different scenarios.

Energies 2020, 13, 246 6 of 21

3. Failed to improve the rule-based control strategy according to the driving cycles. In this research, the control threshold can be customized to mitigate battery degradation at various driving cycles [14,15]. 4. Failed to investigate the combination among the HESS size configuration, topology, and the Energies 2020, 13, x FOR PEER REVIEW 6 of 21 control strategy. In our research, we integrated them together, and presented the quantitative battery degradationThis paper is given is organized across di ffaserent follows. scenarios. Section 2 stresses the topology structure of the proposed HESSThis and paper describes is organized the working as follows. modes Section in both2 stresses driving the conditions topology structure and braking of the proposedconditions. HESS The andstrategy describes is presented the working in Section modes 3. in It bothis a drivingrule-based conditions control andstrategy, braking which conditions. matches The the strategyproposed is presentedHESS closely. in Section In Section3. It 4, is we a rule-based explain the control battery strategy, degradation which model, matches which the is proposed chosen as HESS the objective closely. Infunction Section of4 ,searching we explain for the the battery key parameters degradation of th model,e control which strategy. is chosen Simulation as the objective results are function shown ofin searchingSection 5. Conclusions for the key parameters and future ofwork the are control in Section strategy. 6. Simulation results are shown in Section5. Conclusions and future work are in Section6. 2. The Topology of the HESS 2. The Topology of the HESS For the purpose of improving the current topology, this study proposes a new semi-active HESS For the purpose of improving the current topology, this study proposes a new semi-active HESS topology (Figure 3). Besides inheriting the advantages in other semi-active topologies, the proposed topology (Figure3). Besides inheriting the advantages in other semi-active topologies, the proposed topology also improves both the discharging and charging efficiency. During the HESS operation, topology also improves both the discharging and charging efficiency. During the HESS operation, there are seven modes in total. All operation situations can be identified as one of seven driving there are seven modes in total. All operation situations can be identified as one of seven driving modes. modes. It covers three modes in driving condition and three modes in braking condition. It covers three modes in driving condition and three modes in braking condition.

Figure 3. Proposed HESS topology. Figure 3. Proposed HESS topology. 2.1. Driving Condition 2.1. Driving Condition The driving condition is the most frequent action for vehicles. During the driving conditions, 4 modesThe ofdriving HESS arecondition divided. is Whenthe most selecting frequent each action individual for vehicles. mode, theDuring control the strategydriving andconditions, topology 4 deactivatemodes of HESS or activate are divided. the switches’ When selecting status by each analyzing individual the power mode, demand, the control battery, strategy and and SC SOCtopology. deactivate or activate the switches’ status by analyzing the power demand, battery, and SC SOC. 2.1.1. Mode 1: The Supercapacitor Working as the Unique Energy Source 2.1.1.When Mode the1: TheSOC Supercapacitoris high enough Working (SOC as the UniqueK0), the Energy SC supplies Source all required power solely. SC SC ≥ The preconditionWhen the 𝑆𝑂𝐶 of this is modehigh enough is the SC (𝑆𝑂𝐶 stores ≥𝐾0 enough), the energy. SC supplies The regenerative all required braking power energysolely. The can chargeprecondition SC to aof high this voltage mode (isSOC theSC SC Kstores0). The enSOCoughSC energy.is equal toThe the regenerative ratio between braking the voltage energy square can ≥ andcharge the SC maximum to a high voltage voltage square.(𝑆𝑂𝐶 ≥𝐾0 In mode). The 1, the𝑆𝑂𝐶 controlled is equal switch to the S2ratio isconnected between the (Figure voltage4). square and the maximum voltage square. In mode 1, the controlled switch S2 is connected (Figure 4).

Figure 4. Mode 1—the SC acts as the unique power source.

2.1.2. Mode 2: The SC and Battery Supply Energy to Motor Load Together

Energies 2020, 13, x FOR PEER REVIEW 6 of 21

This paper is organized as follows. Section 2 stresses the topology structure of the proposed HESS and describes the working modes in both driving conditions and braking conditions. The strategy is presented in Section 3. It is a rule-based control strategy, which matches the proposed HESS closely. In Section 4, we explain the battery degradation model, which is chosen as the objective function of searching for the key parameters of the control strategy. Simulation results are shown in Section 5. Conclusions and future work are in Section 6.

2. The Topology of the HESS For the purpose of improving the current topology, this study proposes a new semi-active HESS topology (Figure 3). Besides inheriting the advantages in other semi-active topologies, the proposed topology also improves both the discharging and charging efficiency. During the HESS operation, there are seven modes in total. All operation situations can be identified as one of seven driving modes. It covers three modes in driving condition and three modes in braking condition.

Figure 3. Proposed HESS topology.

2.1. Driving Condition The driving condition is the most frequent action for vehicles. During the driving conditions, 4 modes of HESS are divided. When selecting each individual mode, the control strategy and topology deactivate or activate the switches’ status by analyzing the power demand, battery, and SC SOC.

2.1.1. Mode 1: The Supercapacitor Working as the Unique Energy Source

When the 𝑆𝑂𝐶 is high enough (𝑆𝑂𝐶 ≥𝐾0), the SC supplies all required power solely. The precondition of this mode is the SC stores enough energy. The regenerative braking energy can charge SC to a high voltage (𝑆𝑂𝐶 ≥𝐾0). The 𝑆𝑂𝐶 is equal to the ratio between the voltage square Energies 2020, 13, 246 7 of 21 and the maximum voltage square. In mode 1, the controlled switch S2 is connected (Figure 4).

Energies 2020, 13, x FOR PEER REVIEW 7 of 21 Figure 4. Mode 1—the SC acts as the unique power source. EnergiesIn 2020 mode, 13, x2, FOR the PEER supercapacitorFigure REVIEW 4. Mode assists 1—the the SC actsbatte asry the to unique reduce power the dischargingsource. power. When7 of the 21 2.1.2. Mode 2: The SC and Battery Supply Energy to Motor Load Together 𝑆𝑂𝐶 is in the range [K2, K0] and the power demand is larger than the power threshold (𝑃), 2.1.2.In Mode mode 2: 2,The the SC supercapacitor and Battery Supply assists Energy the batte to Motorry to reduce Load Together the discharging power. When the both Inthe mode battery 2, theand supercapacitorsupercapacitor assistswork as the the battery energy to source. reduce The the power discharging distribution power. strategy When will the 𝑆𝑂𝐶 is in the range [K2, K0] and the power demand is larger than the power threshold (𝑃), SOC be shownis in in the the rangenext section. [K2, K0] Here, and thethe powercontrolled demand switch is largerS2 is connected than the power(Figure threshold 5). (P ), bothSC the battery and supercapacitor work as the energy source. The power distribution strategyThreshold will both the battery and supercapacitor work as the energy source. The power distribution strategy will be shown in the next section. Here, the controlled switch S2 is connected (Figure 5). be shown in the next section. Here, the controlled switch S2 is connected (Figure5).

Figure 5. Mode 2—both the battery and supercapacitor discharge. Figure 5. Mode 2—both the battery and supercapacitor discharge. 2.1.3. Mode 3: The BatteryFigure Acts5. Mode as the2—both Unique the batteryPower andSource supercapacitor discharge. 2.1.3. Mode 3: The Battery Acts as the Unique Power Source 2.1.3.In Mode this mode,3: The Batteryonly battery Acts ascharges the Unique the motor. Power There Source is no current flow between the battery and the SC.In thisIn this mode, mode, only there battery is chargesno energy the loss motor. on Therethe DC/DC is no current converter. flow This between mode the can battery be triggered and the In this mode, only battery charges the motor. There is no current flow between the battery and SC.when In one this of mode, the following there is no two energy conditions loss on is themet: DC (a)/DC The converter. SC does not This have mode enough can be energy triggered stored; when (b) the SC. In this mode, there is no energy loss on the DC/DC converter. This mode can be triggered onethe SC of thehas following sufficienttwo energy conditions stored, isand met: the (a) vehicle The SC demanded does not havepower enough is lower energy than stored; the 𝑃 (b) the when one of the following two conditions is met: (a) The SC does not have enough energy stored; (b) SCHere, has the su fficontrolledcient energy switch stored, S1 is and connected the vehicle (Figure demanded 6). power is lower than the Pthreshold Here, the controlledthe SC has switch sufficient S1 is energy connected stored, (Figure and6 ).the vehicle demanded power is lower than the 𝑃 Here, the controlled switch S1 is connected (Figure 6).

Figure 6. Mode 3—the battery acts as a unique power source. 2.1.4. Mode 4: The Battery Supplies Power to the Motor Load and SC Simultaneously 2.1.4. Mode 4: The BatteryFigure Supplies 6. Mode Power 3—the tobattery the Motor acts as Load a unique and power SC Simultaneously source. In mode 4, the lithium battery supplies energy to both the motor load and SC simultaneously. In mode 4, the lithium battery supplies energy to both the motor load and SC simultaneously. This2.1.4. mode Mode can 4: beThe activated Battery whenSupplies the conditionsPower to the are Motor satisfied Load at the and same SC Simultaneously time: (a) The vehicle demanded This mode can be activated when the conditions are satisfied at the same time: (a) The vehicle In mode 4, the lithium battery supplies energy to both the motor load and SC simultaneously. demanded power is lower than 𝑃; (b) 𝑆𝑂𝐶 is lower than K2. Here, the controlled switch S1 This mode can be activated when the conditions are satisfied at the same time: (a) The vehicle is connected (Figure 7). demanded power is lower than 𝑃; (b) 𝑆𝑂𝐶 is lower than K2. Here, the controlled switch S1 is connected (Figure 7).

Energies 2020, 13, 246 8 of 21 Energies 2020, 13, x FOR PEER REVIEW 8 of 21 powerEnergies 2020 is lower, 13, x thanFOR PEERPthreshold REVIEW; (b) SOCSC is lower than K2. Here, the controlled switch S1 is connected8 of 21 (Figure7).

Figure 7. Mode 4—the battery supplies power to the motor load and SC simultaneously. Figure 7. Mode 4—the battery supplies power to the motor load and SC simultaneously. 2.2. BrakingFigure Condition 7. Mode 4—the battery supplies power to the motor load and SC simultaneously. 2.2. Braking Condition 2.2. BrakingThere areCondition two main controlled targets in the braking condition. Firstly, the braking energy shouldThere be harvested are two main as much controlled as possible; targets secondly, in the braking in order condition. to protect Firstly, the battery, the braking the battery energy should There are two main controlled targets in the braking condition. Firstly, the braking energy beavoid harvested being charged as much frequently as possible; in braking secondly, conditions. in order to protect the battery, the battery should avoid beingshould charged be harvested frequently as much in braking as possible; conditions. secondly, in order to protect the battery, the battery should 2.2.1.avoid Mode being 5:charged Both the frequently Braking Energyin braking and conditions. Battery Charges the SC 2.2.1. Mode 5: Both the Braking Energy and Battery Charges the SC In this mode, all regenerative braking energy flows into the SC. In the meantime, the battery also 2.2.1.In Mode this mode,5: Both allthe regenerative Braking Energy braking and Battery energy Charges flows into the the SC SC. In the meantime, the battery charges the SC. This mode can be activated when the condition is satisfied: The 𝑆𝑂𝐶 is lower than also chargesIn this mode, the SC. all This regenerative mode can braking be activated energy when flows the into condition the SC. In is the satisfied: meantime, The SOCthe batterySC is lower also K1, which aims to resume the SC energy as much as possible. Here, the controlled switch S2 is thanchargesK1, the which SC. aimsThis mode to resume can be the activate SC energyd when as much the condition as possible. is satisfied: Here, the The controlled 𝑆𝑂𝐶 is switch lower S2than is connected (Figure 8). connectedK1, which (Figureaims to8 ).resume the SC energy as much as possible. Here, the controlled switch S2 is connected (Figure 8).

Figure 8. Mode 5—both the braking energy and battery charge the SC. Figure 8. Mode 5—both the braking energy and battery charge the SC. 2.2.2. Mode 6: The SC Harvests the Braking Energy Solely 2.2.2. Mode 6: The FigureSC Harvests 8. Mode the 5—both Braking the Energybraking energySolely and battery charge the SC. Compared with mode 5, the SC absorbs the energy from the regenerative braking system solely in mode2.2.2.Compared Mode 6. It is 6: the The with most SC mode Harvests common 5, the the mode SC Braking absorbs during Energy the the energy braking Solely from process. the regenerative Here, the controlled braking system switch solely S2 is connectedin mode 6. (FigureIt is the9 most). common mode during the braking process. Here, the controlled switch S2 is Compared with mode 5, the SC absorbs the energy from the regenerative braking system solely connected (Figure 9). in mode 6. It is the most common mode during the braking process. Here, the controlled switch S2 is connected (Figure 9).

Energies 2020, 13, x FOR PEER REVIEW 9 of 21

Energies 20202020,, 1313,, 246x FOR PEER REVIEW 99 of of 21

Figure 9. Mode 6—the SC harvests the braking energy solely. Figure 9. Mode 6—the SC harvests the braking energy solely. 2.2.3. Mode 7: The BatteryFigure Harvests 9. Mode the 6—the Braking SC harvests Energy the Solely braking energy solely. 2.2.3. Mode 7: The Battery Harvests the Braking Energy Solely 𝑆𝑂𝐶 ≥𝐾0 2.2.3.After Mode the 7: TheSC isBattery charged Harvests to full the ( Braking Energy) by regenerative Solely braking energy, the SC has no availableAfter space the SC to store is charged the extra to fullbraking (SOC energy.SC K The0) by HESS regenerative controls the braking switch energy, S2 to be the disconnected SC has no ≥ availableand switchAfter space the S1 toSC to be storeis connected.charged the extra to In brakingfull this (𝑆𝑂𝐶 mode, energy. ≥𝐾0 the Thebattery) by HESS regenerative begins controls to harvest thebraking switch the energy, S2regenerative to be the disconnected SC braking has no andavailableenergy. switch In space other S1 to to previous be store connected. the literature, extra In braking this either mode, energy. the thebatte The batteryry HESS or the begins controls SC acts to harvest asthe the switch only the S2 regenerativepower to be source, disconnected braking which energy.willand harvestswitch In other S1 the to braking previous be connected. energy. literature, InHowever, this either mode, thethey the battery cann batteryot or realize the begins SC the acts to balance harvest as the between only the regenerative power battery source, protection braking which willandenergy. harvestredundant In other the braking brakingprevious energy energy. literature, utility. However, either Mode theythe 7 batteis cannot thery action or realize the following SC the acts balance as mode the between only 6 (Figure power battery 10). source, There protection which is an andextremewill redundantharvest situation the brakingbraking when energyenergy.the battery utility. However, driving Mode they downhill 7 is cann theot action at realize a long following the distance. balance mode Because between 6 (Figure of battery the 10 ).regenerative Thereprotection is an extremebraking,and redundant situationthe battery braking when can energy thebe fully battery utility. charged. driving Mode In downhillth 7 is situation,the action at a long both following distance. S1 and mode S2 Because are 6 (Figuredisconnected. of the 10). regenerative There is an braking,extreme situation the battery when can bethe fully battery charged. driving In downhill this situation, at a long both distance. S1 and S2 Because are disconnected. of the regenerative braking, the battery can be fully charged. In this situation, both S1 and S2 are disconnected.

Figure 10. Mode 7—the battery harvests the braking energy solely. Figure 10. Mode 7—the battery harvests the braking energy solely. Across the aboveFigure seven 10. modes,Mode 7—the the switchesbattery harvests S1 and the S2 braking are the energy key components solely. to control the current flowflow direction and route. In summary, the switch S1 is thethe connectionconnection between the battery and theAcross motor. the Onceabove the seven energy modes, fl flowow thetransfer switches between S1 and the S2 battery are the an and keyd motor, motor, components S1 will beto controlconnected. the Incurrent contrast, flow switch direction S2 is and the route. connection In summary, between the supercapacitorswitch S1 is the and connection motor. Once between the energy the battery flow flow transferand the betweenmotor. Once thethe batterybatterythe energy andand fl motor,motor,ow transfer S2S2 willwill between bebe connected.connected. the battery and motor, S1 will be connected. In contrast,K0, K1 andswitchK2 S2 are is the theSOC connectionSC thresholds— betweenP thresholdthe supercapacitor(0.25 ≤ K2 ≤ andK1 ≤ motor.K0 ≤ 1).OnceK0 the is the energy threshold flow K0, K1 and K2 are the 𝑆𝑂𝐶 thresholds—Pthreshold (0.25 ≤ K2 ≤ K1 ≤ K0 ≤ 1). K0 is the threshold above which the SC is regarded as fully charged; K1 is the SOC threshold above which the SC stops transferabove which between the SCthe isbattery regarded and as motor, fully S2charged; will be K connected.1 is the SOC threshold above which the SC stops accepting the current from the𝑆𝑂𝐶 battery. K2 is the SOCthresholdthreshold≤ under≤ which≤ ≤ the SC is not allowable acceptingK0, K the1 and current K2 are from the the battery. thresholds— K2 is theP SOC threshold (0.25 K 2under K1 which K0 the1). SCK0 is notthe allowablethreshold toabove discharge. which the During SC is the regarded range [asK2, fullyK1) charged; of SOCSC K, P1 thresholdis the SOCis the threshold demarcation above point, which which the SC decides stops to discharge. During the range [K2, K1) of 𝑆𝑂𝐶, Pthreshold is the demarcation point, which decides whether the battery charges the SC or not. In the meantime, Pthreshold also decides when the SC begins whetheraccepting the the battery current charges from the the battery. SC or not. K2 isIn the the SOC meantime, threshold Pthreshold under also which decides the when SC is thenot SCallowable begins to assist the battery. The switch S1 is the connection between the battery and the motor. Once the to assistdischarge. the battery. During Thethe switchrange [S1K2, is K the1) of connection 𝑆𝑂𝐶, Pthreshold between is the the demarcation battery and point, the motor. which Once decides the energy flow transfers between the battery and motor, S1 will be connected. In contrast, switch S2 is the energywhether flow the batterytransfers charges between the the SC battery or not. andIn the motor, meantime, S1 will P thresholdbe connected. also decides In contrast, when the switch SC begins S2 is connection between the supercapacitor and motor. Once the energy flow transfers between the battery tothe assist connection the battery. between The the switch supercapacitor S1 is the connection and moto r.between Once the the energy battery flow and transfers the motor. between Once the and motor, S2 will be connected. The type of controlled switch is IRGP4067DPBF [37]. batteryenergy flowand motor, transfers S2 betweenwill be connected. the battery The and ty pemotor, of controlled S1 will be switch connected. is IRGP4067DPBF In contrast, switch [37]. S2 is the connection between the supercapacitor and motor. Once the energy flow transfers between the 2.3.battery Vehicle and Model motor, Specification S2 will be connected. The type of controlled switch is IRGP4067DPBF [37].

2.3. Vehicle Model Specification

Energies 2020, 13, 246 10 of 21

2.3. Vehicle Model Specification Energies 2020, 13, x FOR PEER REVIEW 10 of 21 As to the demanded power calculation, this paper calculates the demanded power as follows: As to the demanded power calculation, this paper calculates the demanded power as follows: power demand : P = [ma + f (v) + mg sin θ] v (3) demand × power demand: 𝑃 = 𝑚𝑎 + 𝑓(𝑣) +𝑚𝑔sin𝜃 ∙𝑣 (3) Coast down curve : f (v) = A + B v + c v2 (4) Coast down curve: 𝑓(𝑣) = 𝐴 +𝐵×𝑣+𝑐∙𝑣× × (4) where m is the vehicle weight, unit: kg. a is the acceleration of vehicle, unit: m/s2. v is the vehicle speed,where m𝑚/ s. is gtheis thevehicle gravitational weight, unit: acceleration, kg. 𝑎 is equalthe acceleration to 9.8 m/s2 .off (vehicle,v) is the unit: coast m/s down2. 𝑣 iscurve the vehicle for the vehicle,speed, m/s. including 𝑔 is the the gravitational rolling resistance acceleration, and the aerodynamic equal to 9.8 m/s resistance.2. 𝑓(𝑣) isf ( thev) is coast the empirical down curve resistance for the equationvehicle, including for a vehicle, the which rolling contains resistance the aerodynamic and the aerodynamic drag and the resistance. rolling resistance 𝑓(𝑣) is [38 the]. A empirical, B and C areresistance the fitted equation parameters for a vehicle, of the coast which down contains curve. theA aerodynamic: Unit is N, B drag: Unit and is Nthes /rollingm, C: Unit resistance is N s 2[38]./m2. · · CoastA, B and down C are is onethe fitted of the parameters most frequent of the tests coast for vehiclesdown curve. and consistsA: Unit is of N, vehicle B: Unit launch is N·s/m, from C a: certainUnit is speedN·s2/m with2. Coast the down engine is ungeared, one of thesimultaneously most frequent tests recording for vehicles the speed and andconsists traveled of vehicle distance launch until from the vehiclea certain stops. speed This with can the be engine done forungeared, different simultan reasons,eously mainly recording targeted the to obtainspeed and valuable traveled information distance aboutuntil the the vehicle general stops. condition This of can the be vehicle done andfor aboutdiffere itsnt interactionreasons, mainly with thetargeted environment. to obtain valuable informationThe battery about and the supercapacitor general condition specification of the vehicl ise introduced and about inits [interaction15]. Table1 with shows the the environment. basic unit parametersThe battery for both and the supercapacitor supercapacitor specification and lithium is battery. introduced in [15]. Table 1 shows the basic unit parameters for both the supercapacitor and lithium battery. Table 1. Unit parameters. Table 1. Unit parameters. Specification Supercapacitor Battery Specification Supercapacitor Battery Capacity ofCapacity unit of unit 2000 2000 F F 44 Ah 44 Ah Maximum voltageMaximum (V) voltage (V) 2.7 2.7 3.6 3.6

FigureFigure 1111 showsshows thethe statisticalstatistical dailydaily drivingdriving distancedistance featuresfeatures [[19].19]. Around 80 percent ofof thethe drivingdriving distance samples have have a a lower lower daily daily trip trip than than 82 82 km. km. Furthermore, Furthermore, 96.6 96.6 km km can can meet meet 85% 85% of ofthe the overall overall driving driving trips. trips. Both Both the the daily daily driving driving di distancestance distribution distribution and and cumulative features areare demonstrateddemonstrated inin FigureFigure 1111..

0.25 1

0.2 0.8

0.15 0.6

0.1 0.4 Cumulative percentage/% Cumulative Distribution percentage/% Distribution 0.05 0.2

0 0 0 15 30 45 60 75 90 105 120 135 150 165 180 195 210 Daily mileage distribution/km Figure 11. Daily driving features. Figure 11. Daily driving features. Taking the NISSAN Leaf as an example, the average measured energy consumption is 171.4 Wh/km on theTaking US06 cycle the NISSAN [19]. Aims Leaf to satisfy as an the example, majority the (e.g., average 85%) of measured the individual energy daily consumption driving requirement is 171.4 (60Wh/km miles), on eventhe US06 until cycle the time [19]. whenAims theto satisfy battery the needs majority to be (e.g., replaced 85%) of (supposing the individual the battery daily driving retires afterrequirement the remaining (60 miles), energy even decreasing until the up time to 70%when of the the battery primary needs capacity), to be the replaced battery (supposing size should the be battery retires after the remaining energy decreasing up to 70% of the primary capacity), the battery size should be configured at least 23.66 kWh. Moreover, the temperature is an important factor that affects the HESS system. However, the temperature influence on the driving range is complicated. For a car with the same configuration, the vehicle’s mileage is various across the different driving

Energies 2020, 13, 246 11 of 21 configured at least 23.66 kWh. Moreover, the temperature is an important factor that affects the HESS system. However, the temperature influence on the driving range is complicated. For a car with the same configuration, the vehicle’s mileage is various across the different driving situation, including the temperature. In this paper, we calculate the energy requirement and configure the battery and SC size under the room temperature environment. According to the previous studying, the supercapacitor units can be set as 76 [19]. The following is a brief introduction to the calculation process: First, the overall energy requirement for the power supply system is calculated by vehicle model and mileage requirement. Secondly, the extreme acceleration driving mode is used to calculate the energy requirement for SC. Thirdly, the energy requirement for the battery is obtained and divided by the battery cell parameters. Therefore, the battery configuration should be set as follows:

EBat = E E (5) All − SC The battery units’ number can be calculated as follows:

EBat NumberBat = . (6) EnergyBat_cell

EBat represents the configured battery package capacity. EAll represents the total energy requirement for the vehicle energy supply source. ESC represents the configured supercapacitor package capacity. EnergyBat_cell is the rated capacity in Wh for each battery unit. Combining the feasible of configured HESS topology, the number of battery cells is chosen as 164. Since the battery package adopts the parallel structure of two cells, referring to Table1, the battery package capacity is 88 Ah (equally, 1 C = 88 A). For the motor, we adopt the same motor as the Nissan Leaf, and for the inverter, its specification is CSI 100-F2T, which support the 110–300 V voltage input [39]. The weight values of the components are described in Table2.

Table 2. Component parameters.

Components Model (kg) Leaf (kg) Base weight (kg) 1462 1462 Battery (kg) 146 181 DC/DC converter (kg) 10 N/A Supercapacitor (kg) 27.4 N/A Total weight (kg) 1645 1643 AN/A 31.91 BN/A 0.11159 CN/A 0.017757

For Nissan leaf, the coast down curve is measured by the Argonne National Laboratory (ANL) [40]. Furthermore, they have the instantaneous power versus the time at different driving cycles. The above table shows that the mass between the leaf and models in the paper is similar. Based on leaf measured data, this study adopts Equation (7) to deduce the power demanded in the configured model.

Weightmodel Emodel = ELea f (7) WeightLea f ×

Emodel represent the energy consumption of the configured, Weightmodel represents the total mass of the configured model, including the DC/DC converter, battery package, and DC/DC converter [41]. Weightlea f represents the total mass of Nissan Leaf. ELea f is the measured energy consumption for Nissan Leaf. Equation (7) shows that the fuel consumption rates between Leaf and HESS models are Energies 2020, 13, 246 12 of 21 approximately equal. Specifically, the leaf can represent the model fuel consumption on the typical driving cycles.

3. Evaluate the Battery Degradation The main object of this research is to explore the SC influence on battery degradation. There are two kinds of battery degradation: Calendar degradation and cycle degradation. Calendar degradation results from time going, and it is not much different for different usage cases. In this paper, only the battery cycle loss is considered. From the above equations, the battery degradation loss can be concluded that the greater the battery discharge power, the faster the battery decaying. According to the previous literature, the battery cycle degradation rate is influenced by the cumulative integral of the circuit and instant discharging value [7]. In HESS, the lithium battery contributes the majority needed energy. However, the supercapacitors can help to decrease the battery degradation rate at the peak power demand period. This paper quantifies the capacity degradation of lithium battery and compares the degradation values between the proposed HESS and the battery solely case. According to previous literature [36], the battery degradation experiential equation is used as follows:

 2  D = α T + β T + γ exp[(δ T + ) Irate] Ah (8) cycle × × × × × Through 0.5 D = µ t exp[ Ea/(R T)] (9) calendar × × − × Dall = Dcycle + Dcalendar (10) where α T2 + β T + γ and µ are pre-exponential factors, T is the absolute temperature, α, β, γ, δ,  × × are fitted parameters of the curve, Irate is the current C rate, AhThrough represents the amount of charge 1 delivered by the battery during cycling, T is the days, Ea is the activation energy in J mol , and R is · − the gas constant. Dcycle , Dcalendar, and Dall are the cycle battery degradation, calendar degradation, and total degradation, respectively. These parameter values are listed in [7]. Once the electric current is flowing between the SC and the battery, the total energy loss of HESS will increase. Approximately all energy flowing from SC can be regarded as the battery output. During the discharging process of HESS, the cumulative energy flowed from SC consumes 1/(η η ) DC/DC × SC times energy from the battery. Here, ηDC/DC and ηSC are DC/DC converter efficiency and SC coulombic efficiency, respectively. In this research, the DC/DC converter efficiency is set as 95%, and the SC coulombic efficiency is set as 92% [42,43].

4. The Control Strategy of the HESS The core part of the control strategy for HESS is the instantaneous control for SC voltage. This is different from the previous literature, in which the formulation is created based on the speed [35].

min(3 Vvehicle, 160) SOCexp = 1 × (11) − 160 r min(3 Vvehicle, 160) Vexp = 1 × Vmax (12) − 160 ×

SOCexp represents the expected SOC of supercapacitor, Vvehicle is the vehicle speed, Vexp is the SC voltage expectation value, and Vmax represents the largest SC voltage. This strategy is easy to control the SC voltage, but there are some drawbacks. In mild driving situations, the vehicle power demand is not high. For the purpose of making good use of battery energy, the battery can act as the unique power source to avoid energy loss in the DC/DC converter and SC. As for the aggressive driving situation, the power demand is much higher than the power demand in a mild driving cycle. In such cases, the SC needs to power the vehicle. Energies 2020, 13, 246 13 of 21

However, different drivers have different driving behaviors, so it is impossible to get a set of fixed control thresholds to meet all kinds of driving situations. Furthermore, the energy capacity of SC is limited, and it is impossible to assist the battery too much. The controller should have the ability to adjust the SOC of SC instantaneously. The previous control strategy is the global optimization to realize the overall optimization for the majority of driving situations, but it cannot realize the best control for every kind of driving cycle. This study comes up with a variable control algorithm to implements the HESS optimized control in different driving situations (UDDS, HWFET, and US06). Energies 2020, 13, x FOR PEER REVIEW 13 of 21 4.1. Control Strategy Diagram This paper uses the decision-tree function to coordinate the power allocation between the This paper uses the decision-tree function to coordinate the power allocation between the supercapacitor and lithium battery (Figure 12). Based on the previous HESS topologies, some new supercapacitor and lithium battery (Figure 12). Based on the previous HESS topologies, some new improvements are added. Further, seven operation modes are divided into driving. When the 𝑆𝑂𝐶 improvements are added. Further, seven operation modes are divided into driving. When the SOC is changing in the range from 0.25 to 1, the controller adopts different power allocation strategiesSC is changing in the range from 0.25 to 1, the controller adopts different power allocation strategies between the battery and SC. between the battery and SC.

Figure 12. Rule-based algorithm. Figure 12. Rule-based algorithm. Different from the chemical application in lithium battery, the supercapacitor keeps the energy by usingDifferent the physical from features. the chemical Theoretically,all application stored in lith energyium battery, in the SC the can supercapacitor be discharged totally.keeps the Because energy of safetyby using reasons, the physical one-quarter features. of theTheoretically, maximum all energy stored does energy not in get the used SC incan the be supercapacitor discharged totally. [44]. 1 BasedBecause on of Equations safety reasons, (1) and (2), one-quarter the working of voltage the maximum of SC is from energyVmax doesto V maxnot[ 21get,44 ].used During in the 2 supercapacitor [44]. Based on Equations (1) and (2), the working voltage of SC is from 𝑉 to 𝑉 real-time control, the HESS chooses the exact working mode based on the demanded vehicle power and instantaneous[21,44]. DuringSOC theSC real-time. Under the control, initial situations,the HESS thechooses switch the S1 exact and S2 working is disconnected. mode based The strategyon the detailsdemanded are listedvehicle as power follows: and instantaneous 𝑆𝑂𝐶 . Under the initial situations, the switch S1 and S2 is Stepdisconnected. 1, judge the The driving strategy or details braking are mode listed based as follows: on the driving action. Step 1, 2, judge if the the vehicle driving is in or the brakin drivingg mode condition, based on mode the driving 1–4 will action. be implemented. The SOCSC, demandedStep 2, power if the andvehicle power is in threshold the driving decide condition, which mode mode is 1–4 activated. will be Including: implemented. The 𝑆𝑂𝐶 , demanded power and power threshold decide which mode is activated. Including:

𝑆𝑂𝐶 is in the range of [K0, 1), which represents the SC is fully charged. In order to keep storage space for the regenerative braking, SC can supply all demanded vehicle power solely.

𝑆𝑂𝐶 is in the range of [K1, K0), which represents the SC owns sufficient energy. If the vehicle demanded power is larger than the threshold (Pthreshold), both the battery and SC supply power together. Mode 2 will be activated. If the vehicle power demand is no larger than the threshold (Pthreshold), mode 3 will be activated. In mode 3, only the battery supplies the energy. The switch S1 is connected.

𝑆𝑂𝐶 is in the range of [K2, K1), which represents the SC stays on the medium energy level. In this situation, if the demanded power is larger than the Pthreshold, model 2 is activated. In this mode, the

Energies 2020, 13, 246 14 of 21

SOCSC is in the range of [K0, 1), which represents the SC is fully charged. In order to keep storage space for the regenerative braking, SC can supply all demanded vehicle power solely. SOCSC is in the range of [K1, K0), which represents the SC owns sufficient energy. If the vehicle demanded power is larger than the threshold (Pthreshold), both the battery and SC supply power together. Mode 2 will be activated. If the vehicle power demand is no larger than the threshold (Pthreshold), mode 3 will be activated. In mode 3, only the battery supplies the energy. The switch S1 is connected. SOCSC is in the range of [K2, K1), which represents the SC stays on the medium energy level. In this situation, if the demanded power is larger than the Pthreshold, model 2 is activated. In this mode, the SC and the battery discharge the energy together. Once the demanded power is larger than Pthreshold, mode 3 will be activated. SOCSC is in the range of [0, K2), which represents the SC has insufficient energy. In this situation, if the demanded power is higher than Pthreshold, the battery supplies the energy to motor solely (mode 3). Otherwise, the battery powers the motor load and charge the SC at the same time (mode 4). However, the maximum discharging power of the battery is no larger than Pthreshold. Step 3, when the vehicle drives in the situation of braking, modes 5–7 will be activated. SOCSC is in the range of [K0, 1), which represents that the SC has sufficient energy. For the purpose of improving energy efficiency, the battery needs to harvest the regenerative braking energy (mode 7). The controller switch S1 is connected. However, in order to protect the battery, mode 7 does not appear frequently. SOCSC is in the range of [K1, K0), which represents the SC stays on the medium energy level. In order words, the SC still has available space to harvest the regenerative braking energy (mode 6). SOCSC is in the range of [0, K1), which represents the SC has insufficient energy. In preparation for the next peak power demand, the SC needs to be charged soon. Besides the regenerative braking energy charging the SC, the battery also charges the SC at constant power. Here, mode 5 is activated.

4.2. Determine the Key Thresholds of the Rule-Based Control Strategy In the above control strategy, seven HESS operation modes are defined based on the HESS status. The factors which decide the mode selection, consist of the power demand, SC SOC. During the multi-comparison, there are four parameters are included: K0, K1, K2 and Pthreshold. The values of the four parameters are different across different cycles. For a certain driving cycle, there is a group of parameters, which can realize the minimum battery current. This paper explores the optimized parameters configuration in the control algorithm, which matches the proposed HESS topology. In the control strategy, there are four parameters (K0, K1, K2 and Pthreshold) to be determined. K0 is the SOCSC threshold above which the SC is regarded as sufficient energy stored (or fully charged). K1 is the SOCSC threshold under which the SC will need the extra charging from the battery when the battery has spare discharging power space. K2 is the SOCSC threshold under which the SC is regarded as insufficient energy stored and stops assisting HESS discharging. Pthreshold is the power threshold, which is used to judge whether the power demand is high or not. For example, if the demanded power is larger than Pthreshold, the demanded power can be regarded as high-power demand. In this research, the control algorithm uses the automatic searching strategy to explore the optimized configuration for the above parameters, which is shown in the Algorithm 1. It is an itinerate loop to find the optimized parameters set for the thresholds. In the control strategy, 1CP means the discharging value of power at which all energy stored in the battery can be discharged out in an hour. For the 24 kWh battery package, 1CP = 24 kW [19]. For K0, its constraint is 0.90 K0 SOC . (13) ≤ ≤ SC,max For K1, its constraint is 0.5 K1 SOC . (14) ≤ ≤ SC,max Energies 2020, 13, 246 15 of 21

For K2, its constraint is [17,22] SOC K2 0.5. (15) SC,min ≤ ≤ Energies 2020, 13, x FOR PEER REVIEW 15 of 21 For Pthreshold, its constraint is 0 Pthreshold 1CP. (16) ≤ ≤

Algorithm 1 Code structure of searching the parameter set. Algorithm 1 Code structure of searching the parameter set. for K0 = 0.9: ∆ :𝑆𝑂𝐶, K SOC for for0 = K0.9:1 =∆ 0.5:: ∆ SC:𝑆𝑂𝐶,max, for K1 = 0.5: ∆ :SOCSC max for K2 = 𝑆𝑂𝐶,, : ∆ :0.5 for K2 = SOCSC,min : ∆ :0.5 for Pthreshold = 0: ∆𝑆𝑂𝐶 :1CP for P = 0: ∆SOC :1CP threshold Calculatestep battery degradation Calculate battery degradation Choose the smaller one after every iteration Choose the smaller one after every iteration result: K0, K1, K2, Pthreshold, which results in the smallest battery degradation. result: K0, K1, K2, Pthreshold, which results in the smallest battery degradation.

5. Results Results InIn theory, theory, the battery can work at a constant disc dischargingharging power if the SC size can be configured configured largelarge enoughenough [ 19[19].]. Combined Combined with with the batterythe battery degradation degradation feature, feature, the battery the canbattery realize can the realize minimum the minimumdegradation degradation when discharging when discharging at a constant at value. a constant The infinite value. SCThe case infinite means SC that case the means SC is that configured the SC islarge configured enough andlarge the enough SC can and supply the unlimitedSC can supply power. unlimited In reality, power. the infinite In reality, SC case the cannot infinite be SC realized case cannotbecause be of realized the actual because cost constraint. of the actual The cost battery cons degradationtraint. The battery gap between degradation infinite gap SC between case and infinite battery SCsolely case case and represents battery solely the largest case represents battery degradation the largest mitigation. battery degradation Taking the HWFETmitigation. as anTaking example, the HWFETFigure 13 as shows an example, the battery Figure current 13 shows in these the threebattery di ffcurrenterent scenarios: in these three Battery different solely, scenarios: optimized Battery HESS, solely,and infinite optimized SC cases. HESS, For and the optimizedinfinite SC HESScases. case, For the optimized battery current HESS can case, avoid the the battery peak current discharging can avoidperiods the e ffpeakectively, discharging such as periods the moment effectively, 300 s and such 625 as s.the As moment for the 300 infinite s and SC 625 case, s. As it for represents the infinite the SCideal case, scenario it represents in which the the ideal battery scenario works in atwhich the average the battery power. works at the average power.

90 Battery solely on HWFET Optimized HESS on HWFET Infinite SC on HWFET 70

50

30

Current/(A) 10

-10

-30

0 100 200 300 400 500 600 700 Time/s Figure 13. Battery current in different scenarios. Figure 13. Battery current in different scenarios. In order to quantify the battery current improvement in different range, Figure 14 shows the In order to quantify the battery current improvement in different range, Figure 14 shows the battery current fractions in each discharging/charging current range. The negative battery current battery current fractions in each discharging/charging current range. The negative battery current shows the regenerative process of braking. Compared with the battery solely case, the optimized HESS shows the regenerative process of braking. Compared with the battery solely case, the optimized reduces the battery charging frequency largely during braking. For example, all high regenerative HESS reduces the battery charging frequency largely during braking. For example, all high braking current (higher than 0.25 C) is avoided. Instead, the braking energy charges the SC rather regenerative braking current −(higher than −0.25 C) is avoided. Instead, the braking energy charges the SC rather than the battery. Similarly, the high battery discharging power period has also been shortened, such as the discharging current range 0.5–0.75 C and higher than 0.75 C. Overall, the optimized HESS moves the peaking discharging and charging current to the mild and small current range, e.g., range 0–0.25 C.

Energies 2020, 13, 246 16 of 21 than the battery. Similarly, the high battery discharging power period has also been shortened, such as the discharging current range 0.5–0.75 C and higher than 0.75 C. Overall, the optimized HESS moves Energiesthe peaking 2020, 13 discharging, x FOR PEER andREVIEW charging current to the mild and small current range, e.g., range 0–0.2516 of 21 C.

80 Battery solely on HWFET Optimized HESS on HWFET 70

60

50

40 Fraction/% 30

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10

0 <-0.25C -0.25C-0 0-0.25C 0.25-0.5C 0.5-0.75C >0.75C Battery current Figure 14. Battery current distribution. Figure 14. Battery current distribution. In this research, a concept of realization percentage is used to evaluate the mitigation effect of the In this research, a concept of realization percentage is used to evaluate the mitigation effect of new proposed optimal HESS system. the new proposed optimal HESS system.

D𝐷Optimal −𝐷DIn f inite 𝑅𝑒𝑎𝑙𝑖𝑧𝑎𝑡𝑖𝑜𝑛Realization percentage =𝑝𝑒𝑟𝑐𝑒𝑛𝑡𝑎𝑔𝑒 = − 100%× 100% (17) (17) D𝐷 −𝐷D × Battery_solely_− In f inite where 𝐷 is the battery degradation value in new proposed HESS system, 𝐷 is the where DOptimalis the battery degradation value in new proposed HESS system, DIn f inite is the battery battery degradation in infinite SC case, and 𝐷 is the battery degradation in battery solely degradation in infinite SC case, and DBattery__solely is the battery degradation in battery solely case. case.In theory, In theory,D 𝐷D ≤ 𝐷D ≤𝐷_, the larger, the the largerRealization the Realization percentage percentageis, the larger is, mitigationthe larger In f inite ≤ Optimal ≤ Battery_solely mitigationon battery degradationon battery degradation can be realized. can be realized. After launching the searching algorithm, four-par four-parameterameter sets sets can can be be deduced for any specific specific driving cycle. Table Table 33 showsshows thethe batterybattery cyclecycle lossloss onon thesethese didifferentfferent tested cycles. According to the simulation, the the HESS HESS can can get as high as 93.79%, 94.44%, and 82.72% of the theoretical mitigation potential of battery degradation on UDDS, HWFET, andand US06,US06, respectively.respectively.

TableTable 3. Searching results for parameters.

UDDSUDDS HWFETHWFET US06 US06 Test distance (km) 71.9 99.0 66.3 Test distanceAverage (km) power (kW) 71.9 2.75 99.05.77 11.17 66.3 Average power (kW)K0 2.750.96 5.770.94 0.98 11.17 K0K1 0.960.9 0.940.82 0.81 0.98 K1K2 0.90.25 0.820.25 0.25 0.81 K2Pthreshold 0.253.12 0.256.24 13.92 0.25 PthresholdBattery degradation (103.12−4) On the tested 6.24 driving cycles 13.92 Battery degradationInfinite SC (%) 37.73 46.37 77.23 4 Optimal (%) On 38.83 the tested 46.79 driving 85.1 cycles (10− ) Battery solely (%) 55.43 53.92 122.78 Infinite SC (%) 37.73 46.37 77.23 Taking our own Optimalrecorded (%) driving cycle 38.83 as an input to 46.79 validate the developed 85.1 control system, Battery solely (%) 55.43 53.92 122.78 Figure 15 shows the speed profile of the trip. This trip is a combined trip, which contains both the city and highway driving features. Figure 16 shows the battery degradation comparison among different HESS. Table 4 gives the cumulative battery degradation values of all kinds of energy storage system. Among all scenarios, the battery size is the same, which is 23.66 kWh. Especially, the energy management algorithm is same for all topologies. Based on Figure 16 and Table 4, the following items can be concluded: (1) The infinite SC case represents the ideal control situation, in which the battery can discharge at the average constant current and realize the least battery degradation. It locates at the lowest position in cyan color. (2) In contrast, the battery solely case represents the worst case, in

Energies 2020, 13, 246 17 of 21

Taking our own recorded driving cycle as an input to validate the developed control system, Figure 15 shows the speed profile of the trip. This trip is a combined trip, which contains both the city and highway driving features. Figure 16 shows the battery degradation comparison among different HESS. Table4 gives the cumulative battery degradation values of all kinds of energy storage system. Among all scenarios, the battery size is the same, which is 23.66 kWh. Especially, the energy management algorithm is same for all topologies. Based on Figure 16 and Table4, the following items can be concluded: (1) The infinite SC case represents the ideal control situation, in which the battery canEnergies discharge 2020, 13 at, x theFOR averagePEER REVIEW constant current and realize the least battery degradation. It locates17 at of the 21 lowest position in cyan color. (2) In contrast, the battery solely case represents the worst case, in which which the battery experiences the largest degradation. In this topology, there is no SC as an assisted the battery experiences the largest degradation. In this topology, there is no SC as an assisted power power source. Generally, the previous two scenarios represent the best and worst battery source. Generally, the previous two scenarios represent the best and worst battery degradation. (3) For degradation. (3) For the simple parallel structure as 1a (refer to Figure 1a), its benefit on mitigating the simple parallel structure as 1a (refer to Figure1a), its benefit on mitigating battery degradation is battery degradation is very limited. The battery degradation is 11.62 × 10−4, which is close to the very limited. The battery degradation is 11.62 10 4, which is close to the battery solely case. It means battery solely case. It means the battery degradation× − mitigation is limited in this case. (4) “Refer 2c” the battery degradation mitigation is limited in this case. (4) “Refer 2c” case is the semi-active HESS case is the semi-active HESS with bidirectional DC/DC converter included, which represents a high with bidirectional DC/DC converter included, which represents a high configuration cost. Except configuration cost. Except for the unlimited SC case, “Refer 2c” is the HESS topology which has the for the unlimited SC case, “Refer 2c” is the HESS topology which has the best battery degradation best battery degradation mitigation. (5) In the proposed HESS, the battery degradation decreased mitigation. (5) In the proposed HESS, the battery degradation decreased from 11.90 10 4 to 8.33 10 4 from 11.90 × 10−4 to 8.33 × 10−4 (reduced by 30%), which is closed “Refer 2c” case.× (6)− “Refer 2a”× case− (reduced by 30%), which is closed “Refer 2c” case. (6) “Refer 2a” case is the fully active HESS with two is the fully active HESS with two bidirectional DC/DC converter included. However, the energy loss bidirectional DC/DC converter included. However, the energy loss of converters leads to the larger of converters leads to the larger energy consumption of the battery. The battery degradation is close energy consumption of the battery. The battery degradation is close to the proposed HESS and refer 2c. to the proposed HESS and refer 2c. (7) “Refer 1b” case is the battery/SC topology in which the (7) “Refer 1b” case is the battery/SC topology in which the bidirectional DC/DC converter included. bidirectional DC/DC converter included. Compared to the “Refer 2a”, the missing of diode leading Compared to the “Refer 2a”, the missing of diode leading to the overflow of the energy, which leads to to the overflow of the energy, which leads to energy loss and increases the battery degradation. energy loss and increases the battery degradation.

40

35

30

25

20

Speed(m/s) 15

10

5

0 0 400 800 1200 1600 2000 2400 2800 3200 Time/s Figure 15. The combined driving cycle. Figure 15. The combined driving cycle. Table 4. The accumulative battery degradation on the tested driving cycle.

0.014 Infinite Battery Proposed Types Refer 1a Refer 1b Refer 2a Refer 2c SCInfinite SC Solely HESS Battery solely Degradation 0.012 7.48Proposed HESS 11.90 8.33 11.62 10.12 8.77 8.08 (10 4) − refer 1a refer 1b 0.01 refer 2a refer 2c 0.008

0.006

0.004 Battery degradation/%

0.002

0 0 400 800 1200 1600 2000 2400 2800 3200 3600 Time/s

Energies 2020, 13, x FOR PEER REVIEW 17 of 21 which the battery experiences the largest degradation. In this topology, there is no SC as an assisted power source. Generally, the previous two scenarios represent the best and worst battery degradation. (3) For the simple parallel structure as 1a (refer to Figure 1a), its benefit on mitigating battery degradation is very limited. The battery degradation is 11.62 × 10−4, which is close to the battery solely case. It means the battery degradation mitigation is limited in this case. (4) “Refer 2c” case is the semi-active HESS with bidirectional DC/DC converter included, which represents a high configuration cost. Except for the unlimited SC case, “Refer 2c” is the HESS topology which has the best battery degradation mitigation. (5) In the proposed HESS, the battery degradation decreased from 11.90 × 10−4 to 8.33 × 10−4 (reduced by 30%), which is closed “Refer 2c” case. (6) “Refer 2a” case is the fully active HESS with two bidirectional DC/DC converter included. However, the energy loss of converters leads to the larger energy consumption of the battery. The battery degradation is close to the proposed HESS and refer 2c. (7) “Refer 1b” case is the battery/SC topology in which the bidirectional DC/DC converter included. Compared to the “Refer 2a”, the missing of diode leading to the overflow of the energy, which leads to energy loss and increases the battery degradation.

40

35

30

25

20

Speed(m/s) 15

10

5

0 0 400 800 1200 1600 2000 2400 2800 3200 Time/s

Energies 2020, 13, 246 Figure 15. The combined driving cycle. 18 of 21

0.014 Infinite SC Battery solely 0.012 Proposed HESS refer 1a refer 1b 0.01 refer 2a refer 2c 0.008

0.006

0.004 Battery degradation/%

0.002

0 0 400 800 1200 1600 2000 2400 2800 3200 3600 Time/s Figure 16. Battery degradation comparison in different HESS.

6. Conclusions This paper proposes a new HESS system, which consists of a novel topology and a customized control algorithm. The improvements include reducing the DC/DC converter size, avoiding frequent discharging and charging to the battery, and maximizing braking energy regeneration. By adding two controlled switches between battery and SC, seven modes are identified based on the demanded power and SOCSC. In the control strategy, different sets of control parameters are found for different driving cycles by using the searching method. For the new HESS system estimation, the battery degradation quantification shows 93.79%, 94.44%, and 82.72% of the theoretical mitigation potential of battery degradation on UDDS, HWFET and US06 are realized, respectively. Using an independent driving cycle as the test cycle, the simulation result shows the battery degradation mitigation reached as high as 30%, larger than the majority of the prior HESS. This result indicates that the HESS topology and control strategy can be optimized together to realize a better battery degradation mitigation target. When comparing the battery degradation with other HESS, the proposed HESS does not need the bi-directional converter, and achieves a competitive battery degradation mitigation result than the majority of the prior HESS. Furthermore, the temperature is a complicated factor that affects the HESS system. The temperature is a complicated factor. For a car with the same configuration, the vehicle’s mileage is not constant across the different driving situations, including the temperature. We prefer to use the security factor to determine the size of the power system. In this paper, we only use the energy required to configure the battery and SC size. In our future research, the temperature factor will be considered in the HESS configuration.

Author Contributions: Total article structure design and writing, C.Z. and D.W.; Literature review and the funding support, B.W.; The battery degradation analysis and rearrange the paper structure, C.Z. and D.W.; The power calculation analysis and reviewed the paper before submitting, C.Z. and F.T. All authors have read and agreed to the published version of the manuscript. Funding: This research received no external funding. Conflicts of Interest: The authors declare no conflict of interest. Energies 2020, 13, 246 19 of 21

References

1. Hannan, M.A.; Hoque, M.M.; Mohamed, A.; Ayob, A. Review of energy storage systems for electric vehicle applications: Issues and challenges. Renew. Sustain. Energy Rev. 2017, 69, 771–789. [CrossRef] 2. Andwari, A.M.; Pesiridis, A.; Rajoo, S.; Martinez-Botas, R.; Esfahanian, V. A review of Battery Electric Vehicle technology and readiness levels. Renew. Sustain. Energy Rev. 2017, 78, 414–430. [CrossRef] 3. Hoque, M.M.; Hannan, M.A.; Mohamed, A.; Ayob, A. Battery charge equalization controller in electric vehicle applications: A review. Renew. Sustain. Energy Rev. 2017, 75, 1363–1385. [CrossRef] 4. Fathabadi, H. Novel fuel cell/battery/supercapacitor hybrid power source for fuel cell hybrid electric vehicles. Energy 2018, 143, 467–477. [CrossRef] 5. Saxena, S.; MacDonald, J.; Moura, S. Charging ahead on the transition to electric vehicles with standard 120V wall outlets. Appl. Energy 2015, 157, 720–728. [CrossRef] 6. Zhang, S.; Xiong, R.; Sun, F. Model predictive control for power management in a plug-in hybrid electric vehicle with a hybrid energy storage system. Appl. Energy 2017, 185, 1654–1662. [CrossRef] 7. Wang, D.; Coignard, J.; Zeng, T.; Zhang, C.; Saxena, S. Quantifying electric vehicle battery degradation from driving vs. vehicle-to-grid services. J. Power Sources 2016, 332, 193–203. [CrossRef] 8. Carkhuff, B.G.; Demirev, P.A.; Srinivasan, R. Impedance-Based Battery Management System for Safety Monitoring of Lithium-Ion Batteries. IEEE Trans. Ind. Electron. 2018, 65, 6497–6504. [CrossRef] 9. Zhang, W.; Nie, J.; Li, F.; Wang, Z.L.; Sun, C. A durable and safe solid-state lithium battery with a hybrid electrolyte membrane. Nano Energy 2018, 45, 413–419. [CrossRef] 10. Serhan, H.A.; Ahmed, E.M. Effect of the Different Charging Techniques on Battery Life-Time: Review. In Proceedings of the 2018 International Conference on Innovative Trends in Computer Engineering, ITCE, Aswan, Egypt, 19–21 February 2018; pp. 421–426. [CrossRef] 11. Lipu, M.S.H.; Hannan, M.A.; Hussain, A.; Hoque, M.M.; Ker, P.J.; Saad, M.H.M.; Ayob, A. A review of state of health and remaining useful life estimation methods for lithium-ion battery in electric vehicles: Challenges and recommendations. J. Clean. Prod. 2018, 205, 115–133. [CrossRef] 12. Ostadi, A.; Kazerani, M.; Chen, S.-K. Hybrid Energy Storage System (HESS) in vehicular applications: A review on interfacing battery and ultra-capacitor units. In Proceedings of the 2013 IEEE Transportation Electrification Conference and Expo (ITEC), Detroit, MI, USA, 16–19 June 2013; IEEE: Piscataway, NJ, USA, 2013; pp. 1–7. [CrossRef] 13. Gallardo-Lozano, J.; Romero-Cadaval, E.; Milanes-Montero, M.I.; Guerrero-Martinez, M.A. Battery equalization active methods. J. Power Sources 2014, 246, 934–949. [CrossRef] 14. Song, Z.; Li, J.; Han, X.; Xu, L.; Lu, L.; Ouyang, M.; Hofmann, H. Multi-objective optimization of a semi-active battery/supercapacitor energy storage system for electric vehicles. Appl. Energy 2014, 135, 212–224. [CrossRef] 15. Shen, J.; Dusmez, S.; Khaligh, A. Optimization of Sizing and Battery Cycle Life in Battery/Ultracapacitor Hybrid Energy Storage Systems for Electric Vehicle Applications. IEEE Trans. Ind. Inform. 2014, 10, 2112–2121. [CrossRef] 16. Ortuzar, M.; Moreno, J.; Dixon, J. Ultracapacitor-Based Auxiliary Energy System for an Electric Vehicle: Implementation and Evaluation. IEEE Trans. Ind. Electron. 2007, 54, 2147–2156. [CrossRef] 17. Burke, A.F. Batteries and Ultracapacitors for Electric, Hybrid, and Fuel Cell Vehicles. Proc. IEEE 2007, 95, 806–820. [CrossRef] 18. Kouchachvili, L.; Yaïci, W.; Entchev, E. Hybrid battery/supercapacitor energy storage system for the electric vehicles. J. Power Sources 2018, 374, 237–248. [CrossRef] 19. Zhang, C.; Min, H.; Yu, Y.; Wang, D.; Luke, J.; Opila, D.; Saxena, S. Using CPE Function to Size Capacitor Storage for Electric Vehicles and Quantifying Battery Degradation during Different Driving Cycles. Energies 2016, 9, 903. [CrossRef] 20. Cao, J.; Emadi, A. A New Battery/UltraCapacitor Hybrid Energy Storage System for Electric, Hybrid, and Plug-In Hybrid Electric Vehicles. IEEE Trans. Power Electron. 2012, 27, 122–132. [CrossRef] 21. Blanes, J.M.; Gutiérrez, R.; Garrigós, A.; Lizán, J.L.; Cuadrado, J.M. Electric Vehicle Battery Life Extension Using Ultracapacitors and an FPGA Controlled Interleaved Buck–Boost Converter. IEEE Trans. Power Electron. 2013, 28, 5940–5948. [CrossRef] 22. Odeim, F.; Roes, J.; Heinzel, A. Power Management Optimization of an Experimental Fuel Cell/Battery/Supercapacitor Hybrid System. Energies 2015, 8, 6302–6327. [CrossRef] Energies 2020, 13, 246 20 of 21

23. Song, Z.; Li, J.; Hou, J.; Hofmann, H.; Ouyang, M.; Du, J. The battery-supercapacitor hybrid energy storage system in electric vehicle applications: A case study. Energy 2018, 154, 433–441. [CrossRef] 24. Rizoug, N.; Mesbahi, T.; Sadoun, R.; Bartholomeüs, P.; Moigne, P.L. Development of new improved energy management strategies for electric vehicle battery/supercapacitor hybrid energy storage system. Energy Effic. 2018, 11, 823–843. [CrossRef] 25. Koubaa, R.; krichen, L. Double layer metaheuristic based energy management strategy for a Fuel Cell/Ultra-Capacitor hybrid electric vehicle. Energy 2017, 133, 1079–1093. [CrossRef] 26. Salmasi, F.R. Control Strategies for Hybrid Electric Vehicles: Evolution, Classification, Comparison, and Future Trends. IEEE Trans. Veh. Technol. 2007, 56, 2393–2404. [CrossRef] 27. Tani, A.; Camara, M.B.; Dakyo, B. Energy Management Based on Frequency Approach for Hybrid Electric Vehicle Applications: Fuel-Cell/Lithium-Battery and Ultracapacitors. IEEE Trans. Veh. Technol. 2012, 61, 3375–3386. [CrossRef] 28. Yuan, Z.; Teng, L.; Fengchun, S.; Peng, H. Comparative Study of Dynamic Programming and Pontryagin’s Minimum Principle on Energy Management for a Parallel Hybrid Electric Vehicle. Energies 2013, 6, 2305–2318. [CrossRef] 29. Trovão, J.P.; Pereirinha, P.G.; Jorge, H.M.; Antunes, C.H. A multi-level energy management system for multi-source electric vehicles—An integrated rule-based meta-heuristic approach. Appl. Energy 2013, 105, 304–318. [CrossRef] 30. Naseri, F.; Farjah, E.; Ghanbari, T. An Efficient Regenerative Braking System Based on Battery/Supercapacitor for Electric, Hybrid, and Plug-In Hybrid Electric Vehicles with BLDC Motor. IEEE Trans. Veh. Technol. 2017, 66, 3724–3738. [CrossRef] 31. Wieczorek, M.; Lewandowski, M. A mathematical representation of an energy management strategy for hybrid energy storage system in electric vehicle and real time optimization using a genetic algorithm. Appl. Energy 2017, 192, 222–233. [CrossRef] 32. Santucci, A.; Sorniotti, A.; Lekakou, C. Power split strategies for hybrid energy storage systems for vehicular applications. J. Power Sources 2014, 258, 395–407. [CrossRef] 33. Wang, L.; Collins, E.G.; Li, H. Optimal Design and Real-Time Control for Energy Management in Electric Vehicles. IEEE Trans. Veh. Technol. 2011, 60, 1419–1429. [CrossRef] 34. Battery Voltage Information—Battery University, BU-303: Confusion with Voltages. Available online: https://batteryuniversity.com/learn/article/confusion_with_voltages (accessed on 28 December 2019). 35. Smith, K.; Earleywine, M.; Wood, E.; Pesaran, A. Battery Wear from Disparate Duty-Cycles: Opportunities for Electric-Drive Vehicle Battery Health Management (Preprint). Available online: https://www.nrel.gov/ docs/fy13osti/54698.pdf (accessed on 28 December 2019). 36. Wang, J.; Purewal, J.; Liu, P.; Hicks-Garner, J.; Soukazian, S.; Sherman, E.; Sorenson, A.; Vu, L.; Tataria, H.; Verbrugge, M.W. Degradation of lithium ion batteries employing graphite negatives and nickel–cobalt–manganese oxide + spinel manganese oxide positives: Part 1, aging mechanisms and life estimation. J. Power Sources 2014, 269, 937–948. [CrossRef] 37. IRGP4750DPBF Infineon Technologies Discrete Semiconductor Products DigiKey. Available online: https://www.digikey.com/product-detail/en/infineon-technologies/IRGP4750DPBF/IRGP4750DPBF- ND/5149324 (accessed on 26 July 2018). 38. Hayes, J.G.; Davis, K. Simplified electric vehicle powertrain model for range and energy consumption based on EPA coast-down parameters and test validation by Argonne National Lab data on the Nissan Leaf. In Proceedings of the 2014 IEEE Transportation Electrification Conference and Expo (ITEC), Dearborn, MI, USA, 15–18 June 2014; IEEE: Piscataway, NJ, USA, 2014; pp. 1–6. [CrossRef] 39. DC-AC Sine Wave Inverters with High Input Voltage Deliver 100VA, ABSOPULSE Electron. Ltd. 2015. Available online: https://absopulse.com/dc-ac-sine-wave-inverters-with-high-input-voltage-deliver-100va- csi-100-f2t-series/ (accessed on 26 July 2018). 40. Research Argonne National Laboratory. Available online: http://www.anl.gov/energy-systems/research (accessed on 26 July 2018).

41. Zhao, C.; Yin, H.; Ma, C. Quantitative Evaluation of LiFePO4 Battery Cycle Life Improvement Using Ultracapacitors. IEEE Trans. Power Electron. 2016, 31, 3989–3993. [CrossRef] 42. Grbovic, P.J.; Delarue, P.; Moigne, P.L.; Bartholomeus, P. A Bidirectional Three-Level DC–DC Converter for the Ultracapacitor Applications. IEEE Trans. Ind. Electron. 2010, 57, 3415–3430. [CrossRef] Energies 2020, 13, 246 21 of 21

43. Sundaram, M.M.; Watcharatharapong, T.; Chakraborty, S.; Ahuja, R.; Duraisamy, S.; Rao, P.T.; Munichandraiah, N. Synthesis, and crystal and electronic structure of sodium metal phosphate for use as a hybrid capacitor in non-aqueous electrolyte. Dalton Trans. 2015, 44, 20108–20120. [CrossRef] 44. Rafik, F.; Gualous, H.; Gallay, R.; Crausaz, A.; Berthon, A. Frequency, thermal and voltage supercapacitor characterization and modeling. J. Power Sources 2007, 165, 928–934. [CrossRef]

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