energies Article An Optimal Slip Ratio-Based Revised Regenerative Braking Control Strategy of Range-Extended Electric Vehicle Hanwu Liu , Yulong Lei, Yao Fu * and Xingzhong Li State Key Laboratory of Automotive Simulation and Control, School of Automotive Engineering, Jilin University, Changchun 130022, China; [email protected] (H.L.); [email protected] (Y.L.); [email protected] (X.L.) * Correspondence: [email protected] Received: 2 February 2020; Accepted: 20 March 2020; Published: 24 March 2020 Abstract: The energy recovered with regenerative braking system can greatly improve energy efficiency of range-extended electric vehicle (R-EEV). Nevertheless, maximizing braking energy recovery while maintaining braking performance remains a challenging issue, and it is also difficult to reduce the adverse effects of regenerative current on battery capacity loss rate (Qloss,%) to extend its service life. To solve this problem, a revised regenerative braking control strategy (RRBCS) with the rate and shape of regenerative braking current considerations is proposed. Firstly, the initial regenerative braking control strategy (IRBCS) is researched in this paper. Then, the battery capacity loss model is established by using battery capacity test results. Eventually, RRBCS is obtained based on IRBCS to optimize and modify the allocation logic of braking work-point. The simulation results show that compared with IRBCS, the regenerative braking energy is slightly reduced by 16.6% and Qloss,% is reduced by 79.2%. It means that the RRBCS can reduce Qloss,% at the expense of small braking energy recovery loss. As expected, RRBCS has a positive effect on prolonging the battery service life while ensuring braking safety while maximizing recovery energy. This result can be used to develop regenerative braking control system to improve comprehensive performance levels. Keywords: range-extended electric vehicle; regenerative braking; optimal slip ratio control; battery capacity loss model; regenerative braking controller; control strategy optimization 1. Introduction With increasingly prominent energy and environmental issues, electric vehicles have developed rapidly in recent years due to their advantages of low pollution-free emission. However, due to the low energy density of battery, short driving range and long charging time, the marketing of battery electric vehicles (BEV) is greatly limited [1,2]. Range-extended electric vehicles (R-EEVs) add auxiliary power units, it can solve the range anxiety from consumers by increasing driving range. In addition, a R-EEV has a certain commercial competitiveness in the future market [3]. The regenerative braking system (RBS) provides an effective way to greatly improve overall electrical performance of R-EEVs [4,5]. Thereby, the regenerative braking control strategy (RBCS) is worthwhile research, and is receiving a good deal of attention. The existing research has focused on RBCS in order to achieve better capacity of the regenerative braking energy. Literature [6] has analyzed the braking force distribution strategy and studied the energy saving potential. Different control strategies are studied to achieve the goals of regeneration efficiency and braking safety in [7–9]. Similar researches also include Literature [10–13], which develop braking torque allocating method to achieve improved braking performance and energy regeneration. In terms of the currently available approaches, it is mainly focused on how to coordinate Energies 2020, 13, 1526; doi:10.3390/en13061526 www.mdpi.com/journal/energies Energies 2020, 13, 1526 2 of 21 Energies 2019, 12, x FOR PEER REVIEW 2 of 21 the regenerative braking torque and mechanical friction to maximize the braking energy recovery while ensuringrecovery thewhile braking ensurin effig ciency.the braking It should efficiency be noted. It should that the be impact noted ofthat regenerative the impact brakingof regenerative current (RCC)braking on current battery (RCC) health on should battery also health be given should suffi alsocient be attention given sufficient and research. attention and research. TheThe otherother focusfocus isis optimization andand the analysis of braking torque distributions strategiesstrategies underunder extremeextreme adhesionadhesion conditions conditions or anor emergencyan emergency braking braking process. process. A revised A controlrevised strategycontrol isstrategy presented is withpresented the front with wheel the front slip ratio wheel consideration slip ratio consideration in [14] to prevent in [14] a frontto prevent wheel a lock-up front wheel and maximize lock-up and the regenerativemaximize the braking regenerative efficiency braking under efficiency low tire–road under low friction tire– conditions.road friction Literature conditions. [15 Literature] proposed [15] an eproposedfficient RBCS an efficient based on RBCS the modifiedbased on nonlinear the modified model nonlinear predictive model control predictive method control to ensure method braking to safety.ensure Inbraking addition, safety. a study In addition, team [16 a ]study built ateam high-precision [16] built a predictivehigh-precision model predictive based on model the o ffbased-line optimizationon the off-line data optimization of the combined data of modelthe combined to solve model the poor to solve real-time the poor problem real-time of the problem optimization. of the Theoptimization. artificial neural The artificial network-based neural controlnetwork mechanism-based control was utilizedmechanism to optimize was utilized the switching to optimize scheme the ofswitching the vehicular scheme braking of the forcevehicular distribution braking was force proposed distribution [17]. was proposed [17]. TheThe previousprevious studies studies have have focused focused more onmore the brakingon the ebrakingfficiency efficiency and maximization and maximization of regenerative of energy,regenerative but the energy, impact but of RCCthe impact on battery of RCC service on battery life is not service considered life is not suffi consideredciently. It meanssufficiently. there isIt stillmeans much there room is still for much optimization room for of optimization RBCS. Therefore, of RBCS. a revised Therefore, regenerative a revised braking regenerative control strategybraking (RRBCS)control strategy is proposed (RRBCS) in this is proposed paper. The in strategy this paper. based The on strategy optimal based slip ratioon optimal (OSR) toslip ensure ratio (OSR) braking to performanceensure braking while performance maximizing while braking maximizing energy recoverybraking andenergy reducing recovery battery and capacityreducing loss battery rate (capacityQloss,%). loss The restrate of(Q thisloss,%). paper The rest is organized of this paper as follows: is organized as follows: InIn SectionSection2, the2, initialthe initial regenerative regenerative braking braking control strategycontrol (IRBCS)strategy is given,(IRBCS) and is the given distribution, and the of thedistribution front and rearof the slip front ratios and and rear allocation slip ratio logics ofand the allocation braking work-point logic of arethe introduced.braking work A simulation-point are modelintroduced. is built A in s Sectionimulation3, and mod theel tire–roadis built adhesionin Section coe 3,ffi andcient the recognition tire–road module adhesion (TACRM) coefficient and doublerecognition fuzzy module logic controller (TACRM) (DFLC) and double are verified fuzzy logic by simulation controller test.(DFLC) In Sectionare verified4, battery by simulation capacity losstest. moduleIn section (BCLM) 4, battery is established. capacity loss The module BCLM (BCLM) uses test is results established. of battery The lifeBCLM decay uses test. test Eventually, results of RRCBSbattery islife proposed. decay test. In SectionEventually,5, the RRCBS e ffectiveness is proposed. and feasibility In section of the5, the proposed effectiveness RRBCS and are feasibility validated byof the test proposed under the RRBCS world light are validated vehicle test by procedure test under (WLTP). the world This light is followed vehicle bytest the procedure conclusion (WLTP). in the finalThis section.is followed by the conclusion in the final section. 2.2. IRBCS Based on OSR 2.1. Control Principle Overview of IRBCS 2.1. Control Principle Overview of IRBCS The research object is a medium-sized R-EEV. As shown in Figure1, the R-EEV is driven by the The research object is a medium-sized R-EEV. As shown in Figure 1, the R-EEV is driven by the front axle. The regenerative braking system consists of two systems: hydraulic braking system and front axle. The regenerative braking system consists of two systems: hydraulic braking system and an electric braking system. Four wheels are equipped with regulating valves, so each wheel can be an electric braking system. Four wheels are equipped with regulating valves, so each wheel can be controlled independently by braking controller. controlled independently by braking controller. Figure 1.1. Structure of range-extendedrange-extended electric vehicle withwith regenerativeregenerative brakingbraking system.system. The optimal control of braking efficiency and energy recovery cannot be guaranteed with fixed slip ratio on different tire–road adhesion conditions. Through monitoring and identification of tire– road adhesion conditions in real time, the OSR is output as the control target value to ensure braking performance [18,19]. Process of IRBCS based on OSR is shown in Figure 2. Energies 2020, 13, 1526 3 of 21 The