«EMR and Inversion-Based Control of a CVT-based Hybrid Truck»

Transcription

1 EMR 17 University Lille 1 June 2017 Summer School EMR 17 Energetic Macroscopic Representation «EMR and Inversion-Based Control of a CVT-based Hybrid Truck» Dr. Clément MAYET 1,2, Dr. Ali CASTAINGS 1,2, Prof. Alain BOUSCAYROL 1,2, Prof. Théo Hofman 3 1 L2EP, University Lille1, France 2 MEGEVH network, France 3 Technical University of Eindhoven, The Netherland

2 Transmission «EMR and IBC of a CVT-based hybrid truck» - Context - FEDER project: Multi-sources hybrid truck with innovative transmission systems 2 2 axes System battery + other Innovative transmission Bat PE1 Carb. ED1 Mth Gearbox PE2 MD2 Objective of the project: Comparison of different structures In the presentation Innovative transmission Multi-sources + + CVT Battery Supercapacitor

3 - Outline EMR and control of the CVT-based hybrid truck Gearbox and CVT principles EMR and control Energy Management Strategy Results 2. EMR and control of an Hybrid Energy Storage System H-ESS principles EMR and control Energy Management Strategy Results 3. Conclusion & Perspectives

4 EMR 17 University Lille 1 June 2017 Summer School EMR 17 Energetic Macroscopic Representation «EMR and control of the CVT-based hybrid truck»

5 Ω(rad/s) Ω(rad/s) «EMR and IBC of a CVT-based hybrid truck» - Gearbox and CVT principles - 5 ICE T ice T blt Cluh TC T Gearbox CVT i bat u bat VSI Ω ice T em PMSM Ω em Ω ice Belt Ω T vt Ω vt Wheel Classical Manual Gearbox Efficiency: 92% Continuous Variable Transmission Efficiency: 85% 90 kw 140 kw 90 kw 140 kw T(Nm) 140 kw T(Nm) 140 kw 90 kw 90 kw

6 - EMR and Control - 6 Electric drive Belt TC CVT FD Wheel Chassis Tice Tblt T Tcvt Tfd Fwh Ftot vhet ICE T ice T blt Cluh TC T Gearbox CVT ICE Bat. Ωice ubat ibat Ted Ωed Ωice k Ω Ωcvt kcvt Ωfd vhet Fbk Brake vhet Fbk-ref vhet Fres Env. i bat u bat VSI Ω ice T em PMSM Ω em Ω ice Belt Ω T vt Ω vt Wheel Ted-ref Tice-ref Tice-ref Tblt-ref T-ref Tcvt-ref Tfd-ref Fwh-ref Ftot-ref vhet-ref kdbk SoCest Strategy vhet-meas Classical manual gearbox Efficiency: 92% Continuous Variable Transmission Efficiency: 85% T dvt k k dvt dvt k dvt T dvt with k dvt [ k1, k2, k3, k4, k5, k6] T cvt k cvt k cvt k cvt T cvt with k cvt [ k 1, k 6] and and k 1 k 1 if if T T 0 0 k 1 k 1 if if T T 0 0

7 - Energy Management Strategy - 7 Electric drive Belt TC CVT FD Wheel Chassis Tice Tblt T Tcvt Tfd Fwh Ftot vhet ICE T ice T blt Cluh T Gearbox ICE Bat. Ωice ubat ibat Ted Ωed Ωice k Ω Ωcvt kcvt Ωfd vhet Fbk Brake vhet Fbk-ref vhet Fres Env. i bat u bat VSI Ω ice T em PMSM Ω em Ω ice Belt Ω T vt Ω vt Wheel Ted-ref Tice-ref Tice-ref Tblt-ref T-ref Tcvt-ref Tfd-ref Fwh-ref Ftot-ref vhet-ref kdbk SoCest Strategy vhet-meas Rules-based strategy [Horrein 2015] [Castaings 2016] Strategy of the hybridization Electric at low speeds ICE at medium speeds + electric assistance ICE at high speed + load the battery Recovery of the braking energy Respect the limitations Strategy of the CVT T(Nm) Ω(rad/s) Ω(rad/s) P-ice(W)

8 - Simulation Results Velocity (km/h) Time (s) 50 ICE power (kw) Traction power (kw) Time (s) Electric power (kw) Time (s) Transmission ratio Time (s) SoC Time (s) Time (s)

9 - Simulation Results - 9 Torque (Nm) DVT Fuel consumption CT-DVT 21,2 L/100km HET-DVT 18,4 L/100km HET-CVT 19,2 L/100km -13,1 % -9,7 % Torque (Nm) CVT Speed (tr/min) Energy saving and losses Hybridization -10/13 % Interest of the CVT? CVT-ICE -4/6 % CVT-eff -6/8 % Speed (tr/min) CVT efficiency!

10 EMR 17 University Lille 1 June 2017 Summer School EMR 17 Energetic Macroscopic Representation «Hybrid Energy Storage System»

11 Power density (W/kg) «EMR and IBC of a CVT-based hybrid truck» - Hybrid Energy Storage System There is no ideal source Advanced flywheel Super Capacitor (SCs) Conventional flywheel Lithium-ion Fuel Ideal source + life time + low cost, Battery as secondary source Autonomy, charging time Cost Life time Multi-sources Lead acid Zn/Air Lithium- Metal Energy density (Wh/kg) H 2 +Fuel cell Battery + Supercapacitor (SCs) Life time Vehicle s viability

12 - EMR and control - 12 ICE T ice T blt TC T CVT Ω ice Ω ice Ω T vt i bat u bat VSI PMSM T em Ω em Belt Ω vt Wheel Battery / SCs + chopper ibat ivsi Bat. SCs. u bat i bat u sc i L i sc u dc m i h u bat u bat i vsi edrive ubat i sc-ref u dc-ref isc idc i dc-ref i vsi-mes usc udc i b-ref Stratégie Mesures

13 - Hybrid Energy Storage System - 13 SCs voltage limitations k lim 1 k lim i hsc-ref/filt >0 i hsc-ref/filt 0 u sc-mes i hsc-ref/filt 0 u sc-m u sc-m1 u sc-m1 u sc u sc-m i b-ref i b-ref/filt i vsi-mes f filt Low-pass filter

14 - Hybrid Energy Storage System Vehicle velocity (km/h) 1 SCs voltage (p.u) u sc-m t(s) u sc-m 0.6 t(s) edrive power (p.u) Battery current (p.u) t(s) t(s)

15 EMR 17 University Lille 1 June 2017 Summer School EMR 17 Energetic Macroscopic Representation «Conclusion & Perspectives»

16 - Conclusion & Perspectives - 16 Conclusion EMR, control, and EMS of the whole system Improvement of the ICE operation BUT increasing of the transmission losses using the CVT Current peaks are reduced using the H-ESS The battery size can be reduced using the H-ESS Perspectives Optimization-based strategy Coupling of the EMS of traction and H-ESS Investigate other innovative transmission systems (EVT, DPG, )

17 EMR 17 University Lille 1 June 2017 Summer School EMR 17 Energetic Macroscopic Representation «BIOGRAPHIES AND REFERENCES»

18 - Authors - 18 Dr. Clément MAYET University Lille 1, L2EP, France PhD in Electrical Engineering at Univ.Lille1 (2016) Research topics: Energy management, traction systems, HEVs, HIL simulation Dr. Ali CASTAINGS University Lille 1, L2EP, France PhD in Electrical Engineering at Univ.Lille1 (2016) Research topics: Energy management of multi-sources vehicles, HIL simulation Prof. Alain BOUSCAYROL University Lille 1, L2EP, MEGEVH, France Coordinator of MEGEVH, French network on HEVs PhD in Electrical Engineering at University of Toulouse (1995) Research topics: EMR, HIL simulation, tractions systems, EVs and HEVs Prof. Théo HOFMAN Technical University of Eindhoven, The Netherland PhD in Mechanical Engineering at TU/e (2007) Research topics: control and system design optimization