Powertrain Design and Modelling for Light and Heavy Duty Vehicles

Transcription

1 1

2 Powertrain Design and Modelling for Light and Heavy Duty Vehicles 2

3 Part 1 Challenges for Electromobility 3

4 20% 4

5 57% NOx 25% PM Joris Besseling 5

6 1 Billion Euro s per Day for import of Oil in Europe Jonathan C. Wheeler 6

7 Top 3 Barriers for EVs High purchase cost Limited driving range Limited charging infrastructure

8 Specific Energy (Wh/kg) x2 x2 x3 x3 Lead Nickel Lithium ? 8 8

9 9

10 Market evolution Purchase price ( ) Driving range (km) 10

11 EAFO 11 THE EUROPEAN ALTERNATIVE FUEL OBSERVATORY Partners: AVERE, VUB, TNO, POLIS, TOBANIA Period:

12 TCO methodology 12

13 Passenger cars medium cars

14 Passenger cars medium cars - subsidy

15 Company cars premium cars

16 Consumer segmentation Fuelling time Purchase price Brand and travel cost 16

17 Private persons Subsidies for EVs (2016) 120% tax reduction for companies 17

18 Infrastructure needs Where is your car during one week? Work Home 18

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20 60.00% Garage and private parking per living unit 50.00% 40.00% 30.00% 20.00% 10.00% 0.00% Vlaanderen Walonië Brussel Source: FOD Economie 20

21 Intelligent roll-out of infrastructure 21

22 Charging Infrastructure Location: Fast Chargers

23 Dynamic Inductive Charging 23

24 Part 2 Powertrain Co-design 24

25 Outline q Introduction of Powertrain topologies q Modeling Approach q Co-design Framework for Powertrains q Case study: Electrified Buses q Conclusions and Future trend 25

26 Outline q Introduction of Powertrain topologies q Modeling Approach q Co-design Framework for Powertrains q Case study: Electrified Buses q Conclusions and Future trend 26

27 Powertrain Topologies: Hybrid EV Vehicles Hybrid Electric Vehicle (HEV) All-Electric Vehicle (AEV) Series-HEV Extended-Range Parallel-HEV Pretransmission Posttransmission Through-the-road (TtR) Series-parallel HEV Complex-HEV Plug-in HEV (PHEV) Battery-based HESS Bat/SC Fuelcell-based HESS FC/Bat FC/SC FC/Bat/SC Series HEV FC: Fuel Cell; Bat: Battery; SC: Supercapacitor 27

28 Powertrain Topologies: Hybrid EV Parallel HEV Series-Parallel HEV 28

29 Powertrain Topologies: Hybrid EV T MAX Hybrid 42.5 % 100 kw 120 kw Compared with ICE vehicle Hybridization: TICE (Nm) Diesel-Electric 32.5 % 40 % 37.5 % 35 % 30 % Conventional 25 % 80 kw 60 kw 40 kw 20 kw ü will reduce the fuel consumption ü will improve the energy efficiency ü will add one or more degree of freedom in the control strategy ü will Improve the dynamic performance ü will minimize the emissions ω ICE (rad/s) 29

30 Powertrain Topologies: BEVs (/SC) + + HE HE SC Bi-directional dc-dc converter - Battery Inverter DC/AC Electric motor Battery HP + - Battery SC + - Multiple-input Bidirectional dc-dc converter DC Link Inverter DC/AC Electric motor HE Battery SC Uni/Bi-directional dc-dc converter Bi-directional dc-dc converter DC Link Inverter DC/AC Electric motor Advantages of Battery (High Energy) /SC or High Power Battery ü Improve the battery lifetime ü More energy efficiency ü High dynamic performance ü Advanced DC/DC converter (i.e. MPC) with high efficiency (up to 96% thanks to WBG technology) o More compactness o High reliability HE: High Energy ; HP: High power: WBG: Wide-Bandgap semiconductors 30

31 Powertrain Topologies: FCHEVs à Disadvantages of FCEV Low dynamic response ( during starting & transient) High cost and size No ability to recover the braking energy Hybridization J Fuel-cell Battery + - Fuel-cell SC Multiple-input converter DC Link Inverter DC/AC Electric motor Transmission Differential Gear + - Fuel-cell Battery DC Link Inverter DC/AC Electric motor Transmission Differential Gear SC Wide range of powertrains topologies or Architectures & Sizing Generic optimization problem!! Source: VUB (Hegazy, 2012): FCHEV based on MPC 31

32 Outline q Introduction of Powertrain topologies q Modeling Approach q Co-design framework for Powertrains q Case study: Electrified Buses q Conclusions and Future trend 32

33 Models Classification Criteria Transients consideration: - Steady State - Dynamic - Quasi-static Calculation Direction - Forward - Backward - Backward-Forward Model Representation - Structural - Functional Causality - Causal - Non-causal Source: A. Bouscayrol (2010) 33

34 Modeling Approach EV Positive Power Flow Battery DC/DC Converter Motor Drive M D Backward approach Given Driving Cycle = Vehicle speed Calculation Direction Positive Power Flow Battery DC/DC Converter Motor Drive M D Forward approach à Vehicle speed is controlled by driver Calculation Direction Low fidelity models Medium fidelity models High fidelity models 34

35 Modeling Approach: Fidelity Low fidelity models Medium fidelity models High fidelity models Time step: 0.5s 1s Time step < ms V_DC I_md I "# = Motor Motor Drive & Drive Motor 1 η(t,ω) $ % & T ref ' () *($,&) V_md1 T REF I_m1 T REAL Motor 1 Detailed efficiency map of components No transients ω T1 w1 q Dynamic models of components ü Transients are considered; ü Low-level control of the power electronics (i.e. the cutting frequency;) ü Dynamic D-q model and control. 35

36 Powertrain Topologies: EMS Rule-based Optimizationbased Learningbased Rule-based Optimization-based Learning-based Deterministic Fuzzy logic Off-line - Thermostat (on/off) - Power follower - Frequency-based - Optimal working condition - Conventional FL - Predictive FL - Adaptive FL - Direct (Dynamic Programming) - Indirect (Pontryagin Minimization Principle) - Derivative-free (DIRECT, SA, GA, PSO) - Gradient (SQP, QP) - Other (Game theory) - Equivalent Consumption Minimization Strategy - Mode l Predictive Control - Support Vector Machine - Reinforcement learning - Artificial neural network Source: J. Van Mierlo & O. Hegazy (2014), book chapter EMS: Energy Management Strategies 36

37 Modeling Approach: Forward for HEV Battery energy consumption Battery Electric motor Fuel consumption Fuel tank Energy management strategy Engine Tice set point TEM set point EMS Clutch Engaged gear Wheel torque, power setpoint Gear box Driver Vehicle Driving cycle: speed setpoint 37

38 Modeling Approach: Backward for HEV Wheel torque, power setpoint EMS Vehicle speed: Driving cycle Vehicle TEM set point Tice set point Electric motor Battery Battery energy consumption Engine Fuel tank Fuel consumption 38

39 Modeling Approach: Forward for HEV V_3AC I_3AC Charger V_bat I_ch I_aux P_aux slope Li-Bat SoC SoH T V_bat I_bat DC/DC Converter & DC BUS V_DC I_md1 Motor Drive 1 V_md1 I_m1 Motor 1 ICE T1 w1 T_ice w_ice Transmission Sys. T_drv w_drv Diff T_wheel front w_wheel Environment Actual Speed Powertrain model High Level Control Reference speed Speed Desired torque Actual speed Driver model/ Speed controller Desired torque Actual speed SOC, SoH, etc. ICE Ref. Torque E Motors Ref Torque REF gear ratio REF Braking Torque Energy Management Strategy 39

40 Modeling Approach: Backward-forward (SHEV) Forward Subsystem Real Achieved Speed Vehicle dynamics P MOTOR REAL Drivetrain Eff=F(P REAL ) P DC BUS REAL DC BUS P GENSET REAL Generator + Rectifier P REAL ICE SHEV Psc Limit? Drivetrain Genset Speed Cycle v a slope Wheel Power Calculation P w T w Gearbox eff=f(t,w) P gb T gb w gb Motor µ=f(t,w) P m Motor Drive eff=f(p) P DCbus v Power flow controller P Genset Generator & Rectifier P ICE ICE Consumption Map T ICE w ICE Consumption SoC Dynamics Psc dc For HEVs, EVs, PHEVs: on-road Light and Heavy Duty DC/DC Converter Psc Supercapacitor ESS Energy Storage P ICE T REF w REF ICE controller LFM: Low Fidelity Models; Medium Fidelity Models; High Fidelity Models 40

41 Powertrain: Modeling and EMS v [km/h] 50 SoC P [kw] time [s] SHEV : An example à On/Off Strategy Pdc Pgen Psc energy savings [%] Kinetic Strategy On-Off Strategy Average Power Strategy Power flow management strategy Energy Savings [%] ESS size [kwh] SC 1,4 1,2 1 0,8 0,6 0,4 0,2 0 ESS size [kwh] Source: R. Barrero (2012) 41

42 Outline q Introduction of Powertrain topologies q Modeling Approach q Co-design framework for Powertrains q Case study: Electrified Buses q Conclusions and Future trend 42

43 Co-design Framework for PTs Powertrain Topology Technology & Sizing Optimal Control (EMS) Powertrain Topology Selection ( HEVs, PHEVs, FCHEVs, EVs, etc.). Layout component optimization (i.e. ICE, battery, Electric Machine, power electronics, CVT, EVT, auxiliaries, etc.). Technology Selection (i.e. battery chemistry, ICE, electric machines, etc.). Optimal sizing (i.e. kwh for battery (Ah?), ICE Power (kw), EM (kw), gearbox (kw),etc.). Optimal power sharing: i.e. between ICE & battery. Fuel consumption minimization. Optimal charging strategy (especially for electric buses): Considering the battery lifetime and limitations; Charging power and time. 43

44 Co-design Framework for PTs Environment Environment Optimal Sizing (i.e. Technology) Optimal Control Optimal Sizing (i.e. Technology) Optimal Control Sequential Approach Nested Approach Environment Environment Optimal Sizing (i.e. Technology) Iterative Approach Optimal Control Topology Sizing + Control Simultaneous Approach Optimal Sizing & Control 44

45 Outline q Introduction of Powertrain topologies q Modeling Approach q Co-design framework for Powertrains q Case study: Electrified Buses q Conclusions and Future trend 45

46 Case Study: Electrified Buses in Brussels Standard Diesel Bus:12m Articulated Diesel Bus:18m 46

47 Case Study: Bus Lines and Requirements Bus Line 86: Feeder bus à 12m Standard Bus Overnight Charging 12hr Autonomy Bus Line 48: Trunk Lineà 18m Articulated Bus Opportunity Charging CC3 Bus Line 17: Neighborhood bus à 12m standard Bus Overnight Charging 12hr Autonomy Pantograph up to 450 kw 47

48 Case Study: Bus Lines and Design Considerations Expected Outcome of the Codesign Framework q Battery technology ( i.e. NMC, LFP, LTO, etc.) q Energy consumption (kwh/km) qbattery Pack Voltage (V) q Charging power (kw) q Charging time (min) à Design Considerations q Road Characteristics q Battery Aging q Charging Scenarios (Overnight or OPPch) q Bus Schedule q Bus Autonomy q Auxiliaries Environment Optimal Sizing (i.e. Technology) Optimal Control Iterative Approach 48

49 Case Study: E-Bus Architecture à High Voltage Batteryà V Energy Management Strategy - HV Battery Pack + EVSE UNIT Electric Flow Mechanical Flow Control Signal 700 V DC/AC Inverter Transmission EM DC/DC Converter Auxiliary Loads 49

50 Case Study: Bus Line 86: Battery sizing Back-Forth Driving Cycle LFP battery (45Ah)/700 Aux. Power à 3kW (Assumption) 50

51 Case Study: Bus Line 86: Battery sizing Autonomy= 12hr DoD: 90% LFP (45Ah) Energy Cons. à ~ 1.8 kwh/km 51

52 Case Study: Charging Power Overnight charging: 40kW Charging time: 4hr15min 200 Overnight Charging: Battery Size (kwh) NMC 20Ah LFP 45Ah 52

53 Case Study: Bus Line 17: Battery sizing Back-Forth Driving Cycle NMC battery (20Ah)/700 V Aux. Power à 3kW 53

54 Case Study: Bus Line 17: Battery sizing Autonomy= 12hr DoD: 90% NMC (20Ah) Average Aux. power à 3kW Battery size: 265kWh for 210 km Overnight charging: 60kW Charging time: 4hr30mins Energy Cons. à ~ 1.3 kwh/km 54

55 Case Study: Bus Line 48: Battery sizing Back-Forth Driving Cycle LTO battery (60Ah)/600 V Average Aux. Power à 3kW 55

56 Case Study: Bus Line 48: OPPch Opportunity charging: 200 both terminals Charging time: 7mins Energy Cons. à ~ 2.97 kwh/km 56

57 Case Study: Summary Bus Line Energy (kwh/km) Charging Scenario Charging time L kwh/km (LFP) OverNCharg: 40kW 4hr 15min L kwh/km (NMC) OverNCharg:60 kw 4 hr 30min L kwh/km (LTO) OPPCharg.: 200 kw 7min One charging Infra for L48 bus line could be integrated into Tram 3 or 4 57

58 Outline q Introduction of Powertrain topologies q Modeling Approach q Co-design Framework for Powertrains q Case study: Electrified Buses q Conclusions and Future trend 58

59 Conclusions Ø Co-design framework is an enabler tool for optimal design and control towards minimum TCO. Ø Average auxiliary power has significant impact on bus energy consumption. Ø LTO is the best option for Opportunity Charging thanks to its high charging current. However, the cost will be one of the key challenges. 59

60 Future Trends Ø Real integration of Opportunity charging into DC Tram/Metro network. Ø Vehicle-to-Grid (V2G) Systems towards smart grid and smart home. Ø On-road Opportunity Charging up to 600 kw. 60

61 Thank you for your attention Contacts Omar Hegazy Thierry Coosemans