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Home , Diesel locomotive, Hydrail, Hydrogen fuel, Union Pearson Express, Wheel arrangement

Article A Conceptualized Powertrain: A Case Study of the Union Pearson Express Route

Mehran Haji Akhoundzadeh 1 , Kaamran Raahemifar 1,2, Satyam Panchal 3, Ehsan Samadani 1, Ehsan Haghi 1 , Roydon Fraser 3 and Michael Fowler 1,*

1 Chemical Engineering Department, University of Waterloo, 200 University Avenue West, Waterloo, ON N2L 3G1, Canada; [email protected] (M.H.A.); [email protected] (K.R.); [email protected] (E.S.); [email protected] (E.H.) 2 Electrical and Computer Engineering, Sultan Qaboos University, P.O. Box: 31, Al-Khound 123, Sultanate of Oman 3 Mechanical and Mechatronics Engineering Department, University of Waterloo, 200 University Avenue West, Waterloo, ON N2L 3G1, Canada; [email protected] (S.P.); [email protected] (R.F.) * Correspondence: [email protected]; Tel.: +1-519-888-4567 (ext. 33415)

 Received: 11 January 2019; Accepted: 29 April 2019; Published: 28 May 2019 

Abstract: A rail (hydrail) powertrain is conceptualized in this study, using drive cycles collected from the currently working on the Union Pearson Express (UPE) railroad. The powertrain consists of three preliminary different subsystems: cell, battery, and systems. A backward design approach is proposed to calculate the time-variable power demand based on a “route simulation data” method. The powertrain components are then conceptually sized according to the calculated duty cycle. The results of this study show that 275 kg of hydrogen is sufficient to satisfy the daily power and demand of a hydrogen with drive cycles similar to the ones currently working on the UPE rail route.

Keywords: hydrogen ; fuel cell ; hydrail powertrain; Li-Ion Batteries

1. Introduction The transportation sector accounts for a significant portion of global (GHG) emissions [1,2]. In 2016 in Canada, 28.3% of the total CO2 emissions were due to the transportation and energy sector [3]. Ontario, one of the highest CO2-emitting provinces in Canada, has been able to reduce its GHG emissions in the sector through replacing coal power plants with renewable power generation technologies. However, the transportation sector has remained a major contributor to GHG emissions in the province [4]. Promoting green public is an important step in moving towards sustainability and reducing GHG emissions [5]. In this context, rail transportation development in Ontario is a key issue for both provincial and federal governments of Canada. GO Transit System (GTS), a regional public transit system serving the Greater Golden Horseshoe region of Ontario, has seven rail lines in the Greater Area (GTA) with diverse transit schedules. Diesel multiple units (DMUs) operating in these lines are the main rail public transportation technologies in Ontario with 60,000 daily ridership. The Union Pearson Express (UPE) line placed on the Kitchener GO rail route also has several common segments with the Lakeshore GO line [6]. A major challenge for rail electrification in an urban area like the GTA is the electricity consumption of the transportation system and the consequent grid stability issues [6]. Contrary to electricity, hydrogen transportation systems will not impose excessive loads to the grid because the hydrogen can be produced at times of surplus power and stored for later use, to meet heat and electricity demands

World Electric Journal 2019, 10, 32; doi:10.3390/wevj10020032 www.mdpi.com/journal/wevj World Journal 2019, 10, x FOR PEER REVIEW 2 of 14 World Electric Vehicle Journal 2019, 10, 32 2 of 14 fluctuations and improve the flexibility of the electricity grid and help in controlling the intermittency of renewable systems [7-12]. specifically for transportation applications. This can also prevent grid fluctuations and improve the

flexibility of the electricity grid and help in controlling the intermittency of renewable systems [7–12]. HydrogenHydrogen transportation transportation is is a amultidimensional multidimensional issu issuee that that can can be analyzed be analyzed from from different different aspects aspects including,including, but but not not limited limited to, to, hydrogen , production, refueling refueling sta stationtion infrastructure, infrastructure, powertrain powertrain componentscomponents topology, topology, sizing, sizing, and and control. control. Evaluating Evaluating the infrastructu infrastructuralral requirements requirements and andenergy energy consumptionconsumption of such of such a system a system is anis an essential essential part part towardstowards commercialization. commercialization. In Inthat that sense, sense, the high the high portionportion of clean of clean electricity, electricity, generated generated by by nuclear nuclear andand renewable sources, sources, in inOntario’s Ontario’s supply supply mix mix providesprovides a unique a unique opportunity opportunity for development development of a of hydrogen a hydrogen transportation transportation system. Figure system. 1, shows Figure 1, showsOntario Ontario electricity electricity supply supply mix in mix 2017 in [13]. 2017 [13].

Wind 6% <1% Solar <1% Gas/Oil 4%

Hydro 26%

Nuclear 63%

Figure 1. Ontario electricity supply mix in 2017 [14].

An analysis by Marin focused on evaluating the impact of hydrogen and electricity supply on the Figure 1. Ontario electricity supply mix in 2017 [14]. cost and GHG emissions of a case study of GO transit along the Lakeshore corridor in Toronto, and this revealedAn analysis that using by scaled-upMarin focused fuel cellson evaluating within the th existinge impact Bombardier of hydrogen ALP-46A and electricity locomotives supply was on reasonablethe cost and [15 GHG]. Furthermore, emissions multipleof a case studies study of have GO investigated transit along di fftheerent Lakeshore design and corridor operation in Toronto, aspects ofand hydrogen this revealed rail systems. that using For scaled-up instance, fuel Li developed cells within a the tramway existing powertrain Bombardier system, ALP-46A which locomotives consisted ofwas a proton-exchangereasonable [15]. Furthermore, membrane fuel multiple cell (PEMFC), studies ahave battery investigated and a different design that and evaluates operation the responsesaspects of ofhydrogen the designed rail systems. energy management For instance, system Li developed [16]. The a designed tramway energy powertrain management system, system which wasconsisted able to of guarantee a proton-exchange safe operating membrane conditions fuel and cell also (PEMFC), increased a battery the lifetime and ofa supercapacitor each power source, that therebyevaluates achieving the responses better overall of the systemdesigned energy ener egyfficiency. management Peng proposed system an[16]. experimental The designed powertrain energy prototypemanagement for system a locomotive was able and to used guarantee PEMFC safe as operating the prime conditions energy source and [also17]. increased The operation the lifetime of the designedof each power locomotive source, was thereby tested achieving on a test better line inoverall Sichuan, system . energy Yamamoto efficiency. tested Peng a proposed hybrid fuel an cellexperimental/battery system powertrain for a railway prototype vehicle, for a which locomoti wasve supposed and used to PEMFC be an equivalent as the prime to current energy systemsource used[17]. inThe operation [18]. The of the authors designed found locomotive an efficiency was of tested 65% for on their a test proposed line in Sichuan, system. HsiaoChina. developed Yamamoto a PEMFCtested a usedhybrid in afuel mini-train cell/battery [19]. system The developed for a railwa systemy vehicle, included which both was hydrogen supposed storage to be andan equivalent lead–acid batteryto current systems, system and used was in tested Japan in [18]. . The Theauthor tests resultsfound showedan efficiency the capability of 65% for of batterytheir proposed/fuel cell hybridsystem. system Hsiao developed was feasible a PEMFC to be implemented used in a mini-t in Taiwanrain [14]. weather The developed conditions system and supplied included stable both power.hydrogen A model storage of and a locomotive lead–acid withbattery PEMFC systems,/battery and hybridwas tested energy in Taiwan. system wereThe test developed results showed in 2018. Inthe this capability study, to of size battery/fuel the components, cell hybrid the authors system usedwas feasible a diesel locomotiveto be implemented WDM-7 in Taiwan which weather is used byconditions the Indian and Railways supplied as stable the baseline power.[ 20A ].model of a locomotive with PEMFC/battery hybrid energy systemThe were first developed prototype in of 2018 a large-scale [19]. In this hydrogen study, to fuel size cell the locomotive components, was the developed authors used in a a Northdiesel Americanlocomotive consortium. class WDM-7 In the which implementation is used by the procedure of the 130 as ton the shunt baseline locomotive, [20]. 300 kW of the powerThe demand first prototype was supplied of a by large-scale means of hydrogenhydrogen fuelfuel cells. cell locomotive The locomotive was was developed fabricated in betweena North 2007American and 2009 consortium. [21]. A group In the of implementation Spanish researchers procedure investigated of the 130 the potentialton shunt of locomotive, fuel cell powertrains 300 kW of World Electric Vehicle Journal 2019, 10, 32 3 of 14 for the railways of Spain between 2010 and 2013. They used three different power management scenarios in a hybrid tramway over the rail routes in Sevilla [22]. In another experimental study, an English research group developed numerical models and used a typical trip and train system as the benchmark [23]. Between the proposed configurations of the study, it turned out that the most optimal topology only needed a tank of 27 kg of hydrogen to complete each trip. However, these studies were not commercially concluded until 2016, when tested the first ever commercial fuel cell train system in [24]. Hydrogen powertrains may be considered as an ambition of future railway transportation, due to their suitability for urban, suburban, and military transportation needs. The development of such complex systems, however, needs interdisciplinary studies for each route. In that sense, this study aims at the conceptual design of different subsystems of a hydrogen powertrain for the UPE route. The reason for such a claim is the necessity to identify different aspects in the development of such a complex system. The aim of this study is to find the approximate sizes of compulsory components used in a hydrail powertrain system. These components consist of Li-ion battery packs and fuel cell stacks. The main goal of such an analysis is to characterize the daily hydrogen demand for the specific rail route. The rest of the manuscript is organized as follows: In Section2, a mechanical model is developed to evaluate the power demand of UPE route with respect to the particular drive cycle. It is assumed that the trains follow a unique drive cycle in each trip. Additionally, the technical specifications for current locomotives are analyzed, as our benchmark, to compare with the resultant duty cycle to evaluate the fidelity of the proposed platform. In Section3, a hybridization scenario is implemented based on the calculations done in Section2. The component sizing is done based on the demanded duty cycle in Section3. Section4 is devoted to the conclusions of the study.

2. Benchmarking Analyzing the demanded driving cycle is the first step in sizing a hybrid powertrain. Once the drive cycle is extracted, the fuel cell can be designed based on the demanded duty cycle and the desired topology. The current UPE’s prime movers “ diesel multiple units (DMUs)” are used as a benchmark for our calculations. Table1 shows the specifications of a self-propelled DMU train. The provided information corresponds to each DMU, whether the trainset is an A- or C-car. An “A-car” configuration consists of two DMU and a C-car configuration consists of three DMU cars synchronized to operate together.

Table 1. Self-Propelled Diesel (DMU) Train Specification [25].

AAR Arrangement 2-B Train Length 25.91 m Track Gauge 1435 mm Train Height 4.3815 m Tare Weight 74,842.741 kg Seating Capacity 60 (56 + 2 wheelchair) Maximum Acceleration 0–32 km/h, 0.56 m/s2 1.1176 m/s2 (Normal) Maximum Deceleration 1.12 m/s2 (Emergency) Maximum Speed 128.75 km/h Number of Powered- 1 /each car Power Output 567 kW Peak Response 3084 Nm

2.1. Drive Cycle Cyclic energy and power demand can be calculated using drive cycle. For our work, UPE drive cycle was extracted using the “Speed Tracker” mobile application with a one second data-sampling rate as shown in Figure2. This application uses the global positioning system (GPS) data to save the World Electric Vehicle Journal 2019, 10, x FOR PEER REVIEW 4 of 14 World Electric Vehicle Journal 2019, 10, x FOR PEER REVIEW 4 of 14 Cyclic energy and power demand can be calculated using drive cycle. For our work, UPE drive Cyclic energy and power demand can be calculated using drive cycle. For our work, UPE drive Worldcycle Electric was extracted Vehicle Journal using2019, the10, 32 “Speed Tracker” mobile application with a one second data-sampling4 of 14 cycle was extracted using the “Speed Tracker” mobile application with a one second data-sampling rate as shown in Figure 2. This application uses the global positioning system (GPS) data to save the rate as shown in Figure 2. This application uses the global positioning system (GPS) data to save the time-dependent velocity of the vehicle on its path. In UPE route, each trip takes 25.5 min and the train time-dependenttime-dependent velocity velocity of of the the vehicle vehicle on on its its path. path. In In UPE UPE route, route, each each trip trip takes takes 25.5 25.5 min min and and the the train train has 10 min of idling at the Union and Pearson stops. From the graph, it turns out that the maximum hashas 10 10 min min of of idling idling at at the the Union Union and and Pearson Pearson stops. stops. From From the the graph, graph, it it turns turns out out that that the the maximum maximum train speed on the route is 127 km/h, which corresponds to the train specification information [25]. traintrain speed speed on on the the route route is is 127 127 km/h, km/h, which which correspon correspondsds to the train specification specification information [[25].25].

Figure 2. Union Pearson Express (UPE)-extracted reputable drive cycle. Figure 2. Union Pearson Express (UPE)-extracted reputable drive cycle. Figure 2. Union Pearson Express (UPE)-extracted reputable drive cycle. FigureFigure3 3shows shows the the route route altitude altitude versus versus time time through through a a UPE UPE route route derived derived from from the the data data output output Figure 3 shows the route altitude versus time through a UPE route derived from the data output ofof thethe SpeedSpeed Tracker application. The The change change in in the the train train altitude altitude occurs occurs beca becauseuse of of the the difference difference in of the Speed Tracker application. The change in the train altitude occurs because of the difference in inthe the altitude altitude of of Toronto Toronto (with (with an an average average of of 76.5 76.5 m) m) and ,Mississauga, Ontario,Ontario, Canada,Canada, wherewhere thethe the altitude of Toronto (with an average of 76.5 m) and Mississauga, Ontario, Canada, where the PearsonPearson AirportAirport isis locatedlocated (with(with anan averageaverage altitudealtitude of of 156 156 m). m). Pearson Airport is located (with an average altitude of 156 m).

Figure 3. Figure 3. AltitudeAltitude ofof thethe UPEUPE route.route. Figure 3. Altitude of the UPE route. 2.2. Duty Cycle

The duty cycle shows the relationship between the power demand and time [26]. Once the duty cycle is obtained, parameters such as peak and average power demand, power transient response, and peak and average energy demand are calculated and used in sizing the powertrain [27]. Duty cycle calculation can be done based on two types of data: “time-at-notch” measurement data and “route simulation data” [26]. In the former method, an event recorder is the preliminary instrument that is used to monitor the train’s power demand. Hence, the parameters of interest are estimated based on statistical analysis. The latter is only used when the drive cycle is highly repeatable and the simulation World Electric Vehicle Journal 2019, 10, x FOR PEER REVIEW 5 of 14

2.2. Duty Cycle The duty cycle shows the relationship between the power demand and time [26]. Once the duty Worldcycle Electric is Vehicleobtained, Journal parameters2019, 10, 32 such as peak and average power demand, power transient response, 5 of 14 and peak and average energy demand are calculated and used in sizing the powertrain [27]. Duty cycle calculation can be done based on two types of data: “time-at-notch” measurement data and can be“route undertaken simulation by data” means [26]. of In analytical the former methods method, an [23 event]. Since recorder the UPE is the drive preliminary cycle does instrument not change duringthat di isff usederent to trips monitor as basedthe train’s on ourpower multiple demand. data Hence, collection the parameters processes, of interest we have are usedestimated a simple theoreticalbased on model statistical to calculate analysis. theThe demandedlatter is only duty used cyclewhen basedthe drive on cycle the collected is highly repeatable drive cycle. and the simulation can be undertaken by means of analytical methods [23]. Since the UPE drive cycle does To develop an applicable model which can represent the dynamic response of the powertrain based not change during different trips as based on our multiple data collection processes, we have used a on thesimple above theoretical mentioned model drive to calculate cycle, we the considered demanded fourdutybasic cycle sourcesbased on of the resistant collected forces: drive cycle. gravitational force, aerodynamicTo develop drag,an applicable rolling resistance,model which and can transient represent force, the dynamic described response by the of following the powertrain equations: based on the above mentioned drive cycle, we considered four basic sources of resistant forces: gravitational force, aerodynamicGravitational drag, rolling force resistance, : FTG = andmg sintransientθ, force, described by the (1) following equations: 1 2 Aerodynamic drag : FAD = ρC Afv , (2) Gravitational force: 𝐹 = 𝑚𝑔sin𝜃2, d (1) dv AerodynamicTransient drag: force F : F=TransientρC A v=, m , (3) dt (2)

Rolling resistance : FRR = (R1 + vR2) mg. (4) Transient force: F =m , (3) In the above equations, g is the acceleration due to gravity (9.81 m/s2), ρ is the air density 3 2 (1.184 kg/m ), Cd is the drag coefficient (0.9388), A f is the frontal area with a value of 15.33 m for the Rolling resistance: 𝐹 = 𝑅 +𝑣𝑅 𝑚𝑔. (4) UPE trains [25], v is the train velocity, and R1, and R 2 are the rolling resistances with values of 0.0019 and 0.000015,In the respectively. above equations, 𝑔 is the acceleration due to gravity (9.81 m/s), 𝜌 is the air density (1.184To calculate kg/m ), the𝐶 weight is the drag of thecoefficient train, it(0.9388), was assumed 𝐴 is the that frontal the area passengers with a value have of an 15.33 average m for weight of 65the kg UPE (per trains person). [25], A𝑣 isC-car the train configuration velocity, and is 𝑅 modeled, and 𝑅 in are this the study.rolling resistances As a result, with the values train of should be able0.0019 to transferand 0.000015, 175(3 respectively.58 + 1) passenger in each trip [28]. It is also assumed that each passenger × carries aTo 5 kg calculate load into the theweight car. of Hence, the train, the it totalwas assumed weight that of a the full passengers train can have be estimated an average as weight 236,779 kg. of 65 kg (per person). A C-car configuration is modeled in this study. As a result, the train should be Moreover, Equation (5) was used to calculate the track grade from Figure4. able to transfer 175 (3 × 58 + 1) passenger in each trip [28]. It is also assumed that each passenger carries a 5 kg load into the car. Hence, the total weight of a full train can be estimated as 236,779 kg. 1 ∆h Track grade : θ = tan− (5) Moreover, Equation (5) was used to calculate the track grade from∆d Figure 4. ∆ Track grade: 𝜃 = tan (5) In this equation, h and d represent the altitude and distance∆ respectively and are both in meter. Figure4 showsIn this theequation, normalized ℎ and time 𝑑 represent variant gradethe altitude for the and UPE distance route. respectively and are both in meter. Figure 4 shows the normalized time variant grade for the UPE route. 0.08

0.07

0.06

0.05

0.04

0.03

Track Grade (rad) 0.02

0.01

0 0 200 400 600 800 1000 1200 1400 1600 Elapsed Time (s)

Figure 4. Normalized time variant grade.

In the next step the total traction force is calculated using Equation (6).

Total force : FTractive = FRR + FTG + FAD + FTransient. (6)

To find the magnitude of torque applied on at each time step, we used a single degree of freedom (1-DOF) dynamic model, Equation (7), with the proportional torque distribution factor of World Electric Vehicle Journal 2019, 10, x FOR PEER REVIEW 6 of 14

World Electric Vehicle Journal 2019, 10, 32 Figure 4. Normalized time variant grade. 6 of 14

In the next step the total traction force is calculated using Equation (6). 0.5 as the only parameter to be considered for the longitudinal acceleration and velocity. The value of Total force: 𝐹 =𝐹 +𝐹 +𝐹 +𝐹. (6) 0.5 is based on the assumption the wheel forces are evenly distributed. To simplify the calculations at To find the magnitude of torque applied on wheels at each time step, we used a single degree of this step, it is also assumed that the wheel is a solid and rigid cylinder with a radius of rw = 0.4572 meter,freedom which (1-DOF) corresponds dynamic tothe model, current Equation train’s (7), wheel with dimensionthe proportional [25]. torque distribution factor of 0.5 as the only parameter to be considered for the longitudinal acceleration and velocity. The value of 0.5 is based on the assumption the wheel forces are evenlydω distributed. To simplify the calculations Wheel tractive torque : T = J w + d r F (7) at this step, it is also assumed that the wheel is a solidw andw rigiddt cylinderf w withTractive a radius of 𝑟 = 0.4572 meter, which corresponds to the current train’s wheel dimension [25]. 2 Here, Jw is wheel inertia in kg m and d is proportional torque distribution factor. Once the Wheel tractive torque:f 𝑇 =𝐽 +𝑑𝑟𝐹 (7) wheel tractive torque is calculated, angular velocity and acceleration can be calculated using the Here, 𝐽 is wheel inertia in kg m2 and 𝑑 is proportional torque distribution factor. Once the demanded drive cycle. Since the positive direction of the axis is fixed to the direction of the tractive torque is calculated, angular velocity and acceleration can be calculated using the velocity, the positive direction for the angular velocity in the proposed backward modeling approach demanded drive cycle. Since the positive direction of the axis is fixed to the direction of the train was assignedvelocity, the to positive be clockwise. direction for the angular velocity in the proposed backward modeling approach Figurewas assigned5 shows to be the clockwise. calculated power demand for trains working in the UPE route. It can be seen that the trainFigure motion 5 shows has the three calculated different power modes: demand acceleration, for trains working deceleration, in the UPE and route. idling. It can Thebe seen braking eventsthat were the identifiedtrain motion as has the three regions different with negativemodes: acceleration, acceleration deceleration, slope. To estimateand idling. the The corresponding braking brakingevents power, were identified for each as two the successive regions with time negative instants acceleration within slope. the braking To estimate region, the corresponding the difference in powerbraking demand power, due for to theeach grading two successive resistance time change instants was within subtracted the braking from theregion, diff erencethe difference in total in power demand.power This demand wasted due powerto the grading can be partlyresistance recovered change was as regenerative subtracted from braking the difference where the in batterytotal is power demand. This wasted power can be partly recovered as regenerative braking where the battery partially charged Figure6. is partially charged Figure 6.

World Electric Vehicle Journal 2019, 10, x FOR PEER REVIEW 7 of 14 FigureFigure 5. Evaluated5. Evaluated duty duty cycle cycle of the current current trains trains working working in UPE in UPE route. route.

FigureFigure 6. 6.Regenerative Regenerative braking power. power.

To analyze the route power demand, a histogram of the power demand during each journey is calculated and shown in Figure 7. As can be seen, the most frequent part of the power demand occurs below the mean power of 283.3 kW and is shown in Figure 5 with a red line. In the next part of this study, we used the mean power as a design criteria value to conceptualize an appropriate topology for the mentioned drive cycle. This would be a good option since the value differs between different routes and can be used in conceptual design step for any individual route.

Figure 7. Histogram of power demand.

To use the estimated power demand for calculating the consumption, we compared our results with the Nippon Sharyo DMU specifications. The “2-B” prime mover has two trucks, and the wheel assemblies are installed on each of its three cars. The “2” truck is installed under the front of the unit and contains two idler axles in a row. Also, there is a “B” located under the rear of each car which has two powered axles. According to the Table 2, each bogie of the current locomotives is equipped with a QSK19-R prime mover. Based on the specification data, the output power of the engine is 567 kW. By comparing this value with the calculated power demand, 400 kW of peak power demand, in this paper, a safety factor of 1.4 is observed showing an acceptable deviation.

World Electric Vehicle Journal 2019, 10, x FOR PEER REVIEW 7 of 14

World Electric Vehicle Journal 2019, 10, 32 7 of 14

To analyze the route power demand,Figure 6. Regenerative a histogram braking of the power. power demand during each journey is calculatedTo and analyze shown the in route Figure power7. As demand, can be a seen, histogram the most of the frequent power demand part of the during power each demand journey occursis belowcalculated the mean and power shown of in 283.3 Figure kW 7. As and can is be shown seen, the in most Figure frequent5 with part a red of the line. power In the demand next part occurs of this study,below we usedthe mean the meanpower powerof 283.3 as kW a designand is shown criteria in valueFigure to5 with conceptualize a red line. In an the appropriate next part of topologythis for thestudy, mentioned we used drivethe mean cycle. power This as would a design be criteria a good value option to conceptualize since the value an diappropriateffers between topology different routesfor and the canmentioned be used drive in conceptual cycle. This would design be step a good for option any individual since the value route. differs between different routes and can be used in conceptual design step for any individual route.

Figure 7. Histogram of power demand. Figure 7. Histogram of power demand. To use the estimated power demand for calculating the hydrogen fuel consumption, we compared To use the estimated power demand for calculating the hydrogen fuel consumption, we our resultscompared with our the results Nippon with the Sharyo Nippon DMU Sharyo specifications. DMU specifications. The “2-B” The “2-B” prime prime mover mover has has two two trucks, and thetrucks, wheel and assemblies the wheel assemblies are installed are oninstalled eachof on its each three of its cars. three The cars. “2” The truck “2” truck is installed is installed under under the front of thethe unit front and of the contains unit and two contains idler axlestwo idler in a axles row. in Also, a row. there Also, is there a “B” is a bogie “B” bogie located located under under the the rear of eachrear car whichof each has car twowhich powered has two axles. powered According axles. Acco to therding Table to 2the, each Table bogie 2, each of thebogie current of the locomotivescurrent is equippedlocomotives with is a equipped QSK19-R with prime a QSK19-R mover. Based prime onmove ther. engine Based on specification the engine data,specification the output data, power the of the engineoutput ispower 567 kW.of the By engine comparing is 567 kW. this By value compar withing thethiscalculated value with the power calculated demand, power 400 demand, kW of peak power400 demand, kW of peak in thispower paper, demand, a safety in this factor paper, of a 1.4safety is observed factor of 1.4 showing is observed an acceptableshowing an deviation.acceptable deviation.

Table 2. Modified preliminary prime mover and final drive specifications.

Component Value Max. Power Out 567 kW Max. Speed (Engine) 3139 rpm Power Out Ratio 4.48 Torque Ratio 4.48 Speed Ratio 1.52 Torque 6764 Nm Max. Angular Velocity 335.10 rad/s Max. Wheel Angular Velocity 78.21 rad/s Final Drive Value 2.61 Max. Road Wheel Torque 8384 Nm

3. Hybridization Scenario Figure8 shows a schematic of the topology of interest in conceptualizing the powertrain based on the collected drive cycle. In the basic topology, the main power supply resource is the fuel cell. The fuel cell should supply the energy demand in different phases. In this scenario, the fuel cell individually provides more than 50% of power demand, which is below the mean power demand (283.3 kW). This means that the power demand at each time step can be broken down into two portions. The first portion should be supplied by the primary resource, which is the fuel cell in this case, and the World Electric Vehicle Journal 2019, 10, 32 8 of 14 second proportion is supplied by the battery package. Although there are several power splitting strategies like frequency separation, this method would be sufficient for evaluating the sensitivity of the World Electric Vehicle Journal 2019, 10, x FOR PEER REVIEW 8 of 14 system. However, the amplitude of the first part should be below or equal to the time-varying average power demand, andTable the 2. second Modified proportion preliminary isprime the remainingmover and final part drive of thespecifications. demand at the mentioned time step. The main goal in this step is to find the number of battery cells based on this scenario. To sustain Component Value a designing goal, it is critical toMax. consider Power thatOut the main bus 567 standard kW voltage in a locomotive should be designed to be in the range of 600–850Max. Speed VDC (Engine) [26 ]. To design 3139 a rpm battery pack that can supply the energy of the main bus, it is necessaryPower to define Out Ratio the voltage of the 4.48 bus as a design criterion. To decrease the demanded current with respectTorque to the Ratio energy demand, the 4.48 bus voltage was assumed to be 850 VDC. Speed Ratio 1.52 In the implementation of the topology, it was assumed that the train should complete the journey Torque 6764 Nm with a full battery pack. At thisMax. stage, Angular preliminary Velocity sizing 335.10 the batteryrad/s package can help the designer. However, it is considered as aMax. design Wheel criterion Angular Velocity of our work, 78.21 rad/s which means that the fuel cell should provide enough energy to completelyFinal Drive maintain Value the energy 2.61 level of battery for the duration of the trip, Max. Road Wheel Torque 8384 Nm meaning that the battery package should become full of charge at the last steps of each trip. Based on this3. and Hybridization using the hydrogen’sScenario Low Heating Value (LHV), we have calculated the hydrogen demand without considering the fuel cell dynamics. In addition, this key criterion will be a base for our future calculationsFigure in 8 theshows development a schematic ofof athe good topology energy of in managementterest in conceptualizing system for the UPE powertrain trains. based on the collected drive cycle. In the basic topology, the main power supply resource is the fuel cell.

FigureFigure 8. Topology 8. Topology of of interest interest in in designing designing thethe po powertrainwertrain for for the the demanded demanded drive drive cycle cycle..

It wasThe fuel also cell assumed should supply that the the battery energy sizingdemand solely in different depends phases. on theIn this main scenario, bus voltage. the fuel cell Since this voltageindividually is 850V, provides the total more battery than pack’s50% of currentpower demand, demand which can be is calculatedbelow the mean by the power Equation demand (8): (283.3 kW). This means that the power demand at each time step can be broken down into two portions. The first portion should be suppliedpower by(W the) primary1052 resource, kW 1000 which W is the fuel cell in this Pack current capacity = = = 1238 A. (8) case, and the second proportion is suppliedPack voltageby the battery(V) package.850 V Although× 1 kW there are several power splitting strategies like frequency separation, this method would be sufficient for evaluating the World Electric Vehicle Journal 2019, 10, 32 9 of 14

To design the battery pack, we analyzed the duty cycle to calculate the difference between time-varying average power demand and the peak power demand. In the proposed topology, it was assumed that batteries connected in series should provide the appropriate VDC level. The demanded transient current should also be provided by adding these serial battery branches in parallel. Hence, using a typical lithium ion battery [29], the number of cells in series and parallel can be calculated based on the following. Cells in Series, nseries: Vnom series pack 850 V n = nom = = 236 cells (9) Vcell 3.6 V Strings in Parallel, nparallel:

parallel = Demanded Current = 1238 A n 5C discharge current o f battery cell 100 A cell (10) = 12.38 cells 12 strings ∼ Total = 236 series 12 strings = 2832 cells (11) cells × The calculation shows that if the portion of fuel cell contribution is subtracted from the battery portion—which is the difference of the maximum power demand and the mean power demand—the required battery pack should have 12 strings in parallel with each string, having 236 cells in series.

3.1. Fuel Cell Stack Calculation In the conceptual design, we take the number of fuel cells as a design criterion. The criteria should be a goal in detailed design as well. This factor can automatically satisfy several other parameters like the minimum hydrogen consumption. In other words, to minimize the hydrogen consumption in each trip, an optimal number of fuel cells should be used in a powertrain depending on the control strategy. However, in this approach, fuel cells in collaboration with the battery packs must provide the powertrain with enough energy demand in all modes of motion. Although the fuel cell individually should supply the time-varying average power demand, as it is working in parallel with the battery pack, as the main energy source, it should be able to provide the necessary power demand to keep the battery pack full until the train is working in its high-frequency portion of its duty cycle. In order to benchmark the size of the fuel cell pack, Table3 shows the specification of the fuel cell module choosing to be used in the powertrain. However, based on the calculations, 14 fuel cell stacks configured in one serial string can supply the mean power portion of the total power demand as well as the other energy-supplying phases.

Table 3. Fuel cell specification used in calculations [30].

Parameter Value Dimension 0.605 0.410 0.265 m × × Weight 61 kg Rated Electrical Power 33 kW Operating Current 0 to 500 ADC Operating Voltage 60 to 120 VDC Peak Efficiency 55% Fuel Dry Hydrogen > 99.98% Oxidant Ambient Air Coolant De-ionized or 60% Ethylene Glycol/Di H2O 10 to + 55 C operating − ◦ Ambient Temperature 40 to + 65 C storage − ◦ (<20 ◦C with automated freeze shutdown feature) World Electric Vehicle Journal 2019, 10, x FOR PEER REVIEW 10 of 14 demand to keep the battery pack full until the train is working in its high-frequency portion of its duty cycle. In order to benchmark the size of the fuel cell pack, Table 3 shows the specification of the fuel cell module choosing to be used in the powertrain. However, based on the calculations, 14 fuel cell stacks configured in one serial string can supply the mean power portion of the total power demand as well as the other energy-supplying phases.

Table 3. Fuel cell specification used in calculations [19].

Parameter Value Dimension 0.605 × 0.410 × 0.265 m Weight 61 kg Rated Electrical Power 33 kW Operating Current 0 to 500 ADC Operating Voltage 60 to 120 VDC Peak Efficiency 55% Fuel Dry Hydrogen > 99.98% Oxidant Ambient Air Coolant De-ionized Water or 60% Ethylene Glycol/Di H2O −10 to + 55 °C operating World Electric VehicleAmbient Journal 2019 Temperature, 10, 32 −40 to + 65 °C storage 10 of 14 (<20 °C with automated freeze shutdown feature)

3.3.3.2. Hydrogen Hydrogen Fuel Fuel Calculation Calculation ToTo calculate calculate the the required required hydrogen, hydrogen, the the lower lower heat heatinging value value (LHV) (LHV) of hydrogen of hydrogen is used is usedover the over higherthe higher heating heating value value(HHV). (HHV). The LHV The of LHV the gaseou of the gaseouss hydrogen hydrogen is 119.96 is MJ/kg 119.96 [30]. MJ/ kgFigure [31]. 9 Figureshows9 theshows energy the consumption energy consumption of the train of during the train a journey during of a journeyone day ofbased one on day the based real world on the duty real cycle. world Itduty is seen cycle. that the It is maximum seen that value the maximum of energy value consum ofption energy is consumptionaround 121 kW is for around that particular 121 kW for duty that cycle.particular In addition, duty cycle. the corresponding In addition, the required corresponding timely hydrogen required timelyconsumption hydrogen was consumption also calculated, was andalso is calculated,presented in and Figure is presented 10. To calculate in Figure the 10 hydrog. To calculateen consumption, the hydrogen it is suffice consumption, to multiply it isenergy suffice consumptionto multiply energywith hydrogen consumption LHV. Fi withgure hydrogen 11 shows LHV.the hydrogen Figure 11 consumption shows the hydrogen for one trip consumption and, from thefor plot, one it trip turns and, out from that thethe plot,train itconsumes turns out 3.6 that kg theof hydrogen train consumes in each 3.6trip. kg According of hydrogen to a inMetrolinx each trip. reportAccording [6], the to total a number report of trips [6 ],per the day total is number154 for weekdays of trips per and day 146 is 154over for the weekdays weekends. and This 146 translatesover the weekends.to a total of This55,442 translates trips per to year. a total This of 55,442is equivalent trips per to year.0.2 tons This of is hydrogen equivalent consumption to 0.2 tons of perhydrogen year. consumption per year.

World Electric Vehicle Journal 2019Figure, 10, x9. FOREnergy PEER consumptionREVIEW of the train during its path. 11 of 14 Figure 9. Energy consumption of the train during its path.

Figure 10. Timely hydrogen consumption. Figure 10. Timely hydrogen consumption.

Figure 11. Hydrogen consumption for one trip.

4. Conclusions In this study, a hybrid fuel cell powertrain was conceptually designed for use in Union Pearson drive cycle in Toronto, Ontario, Canada. The repeatable drive cycle of the Union Pearson Express trains was extracted and used in obtaining the time-dependent power demand profile, “duty cycle”. To size the powertrain, four major subsystems were estimated as the primary components of interest, and the appropriate commercialized subsystems put forward in the calculations to investigate the feasibility of the implementing the topology of interest. The calculations showed that a hydrogen/battery hybrid powertrain was able to generate an average power demand of 283.3 kW and peak power demand of 1335 kW, which was needed to meet the drive cycle of the trains and the route geometry requirement based on an empirical data extracted from the working trains. In the development of the powertrain topology, the fuel cell packs were designed to supply the time average power demand of about 283.3 kW. The main reason was that the highest percentage of power demand shows to be lower than this value. Another reason for such a scenario was that the batteries can respond faster than the fuel cells. The fuel cell and battery pack were capable of satisfying the route energy demand. The battery packs were totally charged at the end of the route, and the regenerative braking portion was also considered in the route energy demand. Finally, the hydrogen demand for the proposed topology was estimated as 275 kg per day, and it turned out that the range of the powertrain, with this World Electric Vehicle Journal 2019, 10, x FOR PEER REVIEW 11 of 14

World Electric Vehicle Journal 2019, 10, 32 11 of 14 Figure 10. Timely hydrogen consumption.

FigureFigure 11. HydrogenHydrogen consumption consumption for for one one trip. trip. 4. Conclusions 4. Conclusions In this study, a hybrid fuel cell powertrain was conceptually designed for use in Union Pearson In this study, a hybrid fuel cell powertrain was conceptually designed for use in Union Pearson drive cycle in Toronto, Ontario, Canada. The repeatable drive cycle of the Union Pearson Express drive cycle in Toronto, Ontario, Canada. The repeatable drive cycle of the Union Pearson Express trains was extracted and used in obtaining the time-dependent power demand profile, “duty cycle”. trains was extracted and used in obtaining the time-dependent power demand profile, “duty cycle”. To size the powertrain, four major subsystems were estimated as the primary components of interest, To size the powertrain, four major subsystems were estimated as the primary components of interest, and the appropriate commercialized subsystems put forward in the calculations to investigate the and the appropriate commercialized subsystems put forward in the calculations to investigate the feasibility of the implementing the topology of interest. feasibility of the implementing the topology of interest. The calculations showed that a hydrogen/battery hybrid powertrain was able to generate an average The calculations showed that a hydrogen/battery hybrid powertrain was able to generate an power demand of 283.3 kW and peak power demand of 1335 kW, which was needed to meet the drive average power demand of 283.3 kW and peak power demand of 1335 kW, which was needed to meet cycle of the trains and the route geometry requirement based on an empirical data extracted from the the drive cycle of the trains and the route geometry requirement based on an empirical data extracted working trains. In the development of the powertrain topology, the fuel cell packs were designed from the working trains. In the development of the powertrain topology, the fuel cell packs were to supply the time average power demand of about 283.3 kW. The main reason was that the highest designed to supply the time average power demand of about 283.3 kW. The main reason was that percentage of power demand shows to be lower than this value. Another reason for such a scenario the highest percentage of power demand shows to be lower than this value. Another reason for such was that the batteries can respond faster than the fuel cells. a scenario was that the batteries can respond faster than the fuel cells. The fuel cell and battery pack were capable of satisfying the route energy demand. The battery The fuel cell and battery pack were capable of satisfying the route energy demand. The battery packs were totally charged at the end of the route, and the regenerative braking portion was also packs were totally charged at the end of the route, and the regenerative braking portion was also considered in the route energy demand. Finally, the hydrogen demand for the proposed topology was considered in the route energy demand. Finally, the hydrogen demand for the proposed topology estimated as 275 kg per day, and it turned out that the range of the powertrain, with this hydrogen was estimated as 275 kg per day, and it turned out that the range of the powertrain, with this volume, will be improved compared to the conventional Trier 4 diesel and their current fuel storage tanks. The developed model can be considered as a semi-empirical method, and the model can be used for similar trains working in a high accelerated drive cycles in GTA.

Author Contributions: This is to notice that the following contribution were conducted with the co-authors during the manuscript preparation: writing, review, and editing of the original paper, M.H.A., S.P., E.S., and E.H.; supervision, professors M.F., K.R., and R.F. Funding: This paper was written with the support of National Science and Engineering Research Council Discovery Grant 261669-2013-RGPIN and Clean Rail Program—. Acknowledgments: We thank Manoj Mathew and Muneendra Prasad Arkhat for their technical supports and during writing this paper. Conflicts of Interest: This statement is to certify that all Authors have seen and approved the manuscript being submitted. We warrant that the article is the Authors’ original work. We warrant that the article has not received prior publication and is not under consideration for publication elsewhere. On behalf of all Co-Authors, the corresponding Author shall bear full responsibility for the submission. This research has not been submitted for publication nor has it been published in whole or in part elsewhere. We attest to the fact that all Authors listed on the title page have contributed significantly to the work, have read the manuscript, attest to the validity and World Electric Vehicle Journal 2019, 10, 32 12 of 14 legitimacy of the data and its interpretation, and agree to its submission to the World Electric Vehicle Journal. All authors agree that author list is correct in its content and order and that no modification to the author list can be made without the formal approval of the Editor-in-Chief, and all authors accept that the Editor-in-Chief’s decisions over acceptance or rejection or in the event of any breach of the Principles of Ethical Publishing in the World Electric Vehicle Journal being discovered of retraction are final. No additional authors will be added post submission, unless editors receive agreement from all authors and detailed information is supplied as to why the author list should be amended.

Nomenclature

Variable Name Units 2 Af frontal area m Cd drag coefficient - df proportional torque distribution factor - E energy kWh FAD aerodynamic drag N FRR rolling resistance N FTG track grade force N FTractive N FTransient transient force N g gravitational constant m/s2 I current A Icap current capacity A h · 2 Jw wheel inertia kg m · m mass kg P power kW R1 rolling resistance coefficient 1 - R2 rolling resistance coefficient 2 - rw wheel radius m t time s Tw wheel torque N m · V voltage V v velocity m/s ∆d change in distance m ∆h change in height (altitude) m θ track grade rad ρ density kg/m3 ωw wheel angular velocity m/s

Acronyms

ADC Ampere CNR Canadian National Railway CPR Canadian Pacific Railway DOF degree of freedom DMUs diesel multiple units GHG greenhouse gas GTS GO Transit System GTA GPS global positioning system GEFC Green Energy and Fuel Cell TPH PEMFC proton-exchange membrane fuel cell UPE Union Pearson Express VDC volt direct current World Electric Vehicle Journal 2019, 10, 32 13 of 14

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