A New Framework for Advancement of Power Management Strategies in Hybrid Electric Vehicles

Document Type : Original Article

Authors

1 Department of Mechanical Engineering, Sharif University of Technology, Tehran, Iran

2 System Design Engineering Faculty, University of Waterloo, 200 University Avenue West, Waterloo, Ontario, Canada

Abstract

Power management strategies play a key role in the design process of hybrid electric vehicles. Electric Assist Control Strategy (EACS) is one of the popular power management strategies for hybrid electric vehicles (HEVs). The present investigation proposes a new framework to advance the EACS. Dynamic Programming method is applied to an HEV model in several drive cycles, and as a result, some optimal operating regions are found. The obtained regions are almost distinct, and consequently, some threshold lines can be defined to separate them. The obtained threshold lines are used to eliminate some parameters of the EACS to reduce its sensitivity to the driving behavior. It is shown that by applying the mentioned modification, the sensitivity of the EACS decreases without a significant increase in the HEV’s FC. All in all, our findings indicate the effectiveness of the proposed methodology to improve the EACS strategy for HEV supervisory control applications.

Keywords


 
7. REFERENCES
 
1. Ceraolo, M., di Donato, A. and Franceschi, G. “A General Approach
to Energy Optimization of Hybrid Electric Vehicles,” IEEE
Transactions on Vehicular Technology, Vol. 57, No. 3, (2008),
1433–1441. 
2. Reddy, N. P., Pasdeloup, D., Zadeh, M. K. and Skjetne, R. “An
Intelligent Power and Energy Management System for Fuel
Cell/Battery Hybrid Electric Vehicle Using Reinforcement
Learning,” In 2019 IEEE Transportation Electrification
Conference and Expo (ITEC), (2019). 
3. Mansour, C. and Clodic, D. “Optimized Energy Management
Control for the Toyota Hybrid System Using Dynamic
Programming on a Predicted Route with Short Computation
Time,” International Journal of Automotive Technology, Vol.
13, No. 2, (2012), 309–324. 
4. Lu, D. and Ouyang, M. “Torque-based optimal acceleration control
for electric vehicle,” Chinese Journal of Mechanical
Engineering, Vol. 27, No. 2, (2014), 319–330. 
5. Guo, H., Wei, G., Wang, F., Wang, C. and Du, S. “Self-Learning
Enhanced Energy Management for Plug-in Hybrid Electric Bus
with a Target Preview Based SOC Plan Method,” IEEE Access,
Vol. 7, (2019), 103153–103166. 
6. Wu, J., Zhang, C. H. and Cui, N. X. “PSO algorithm-based parameter
optimization for HEV powertrain and its control strategy,”
International Journal of Automotive Technology, Vol. 9, No. 1,
(2008), 53–59. 
7. Wu, X., Cao, B., Wen, J. and Bian, Y. “Particle swarm optimization
for plug-in hybrid electric vehicle control strategy parameter,” In
IEEE Vehicle Power and Propulsion Conference, 2008. VPPC
’08, (2008). 
8. Guo, Q., Zhao, Z., Shen, P., Zhan, X. and Li, J. “Adaptive optimal
control based on driving style recognition for plug-in hybrid
electric vehicle,” Energy, Vol. 186, (2019), 115824.
doi.org/10.1016/j.energy.2019.07.154 
9. Li, H., Ravey, A., N’Diaye, A. and Djerdir, A. “Online adaptive
equivalent consumption minimization strategy for fuel cell hybrid
electric vehicle considering power sources degradation,” Energy
Conversion and Management, Vol. 192, (2019), 133–149. 
10. Haufmann, B., Barroso, D., Vidal, C., Bruck, L. and Emadi, L. “A
Novel Multi-Mode Adaptive Energy Consumption Minimization
Strategy for P1-P2 Hybrid Electric Vehicle Architectures,” In
2019 IEEE Transportation Electrification Conference and Expo
(ITEC), (2019). 
11. Cui, L., Jianhua, G., Wei, Z. and Kangjie, L. “Research on AECMS
Energy Management Strategy of PHEV,” In 2019 IEEE 3rd
Information Technology, Networking, Electronic and
Automation Control Conference (ITNEC), (2019). 
12. Hmidi, M. E., Salem, I. B. and Amraoui, L. E. “Analysis of rulebased
parameterized control strategy for a HEV Hybrid Electric Vehicle,” In 2019 19th International Conference on Sciences and Techniques of Automatic Control and Computer Engineering (STA), (2019). 
13. Banvait, H., Anwar, S. and Chen, Y. “A rule-based energy
management strategy for Plug-in Hybrid Electric Vehicle
(PHEV),” In American Control Conference, (2009). 
14. Ma, K., Wang, Z., Liu, H., Yu, H. and Wei, C. “Numerical
Investigation on Fuzzy Logic Control Energy Management
Strategy of Parallel Hybrid Electric Vehicle,” Energy Procedia,
Vol. 158, (2019), 2643–2648. 
15. Safaei, A., Ha’iri-Yazdi, M. R., Esfahanian, V., Esfahanian, M.,
Tehrani, M. M., and Nehzati, H. “Designing an intelligent control
strategy for hybrid powertrains utilizing a fuzzy driving cycle
identification agent,” Proceedings of the Institution of
Mechanical Engineers, Part D: Journal of Automobile 
Engineering, (2014), 1–20.
16. Li, G., and Görges, D. “Fuel-Efficient Gear Shift and Power Split 
Strategy for Parallel HEVs based on Heuristic Dynamic
Programming and Neural Networks,” IEEE Transactions on
Vehicular Technology, (2019), 9519 - 9528. 
17. Nidubrolu, K., Dhamija, L., Chaudhary, P. and Kirtane, C. “An
Optimal Rule Based Energy Management System for a Hybrid
Electric 2-Wheeler Based on Dynamic Programming Technique,”
SAE International, Warrendale, PA, SAE Technical Paper 201926–0128,
(2019).
18. Škugor, B., Deur, J., Cipek, M., and Pavković, D., “Design of a
power-split hybrid electric vehicle control system utilizing a rulebased
controller and an equivalent consumption minimization
strategy,” Proceedings of the Institution of Mechanical 
Engineers, Part D: Journal of Automobile Engineering, Vol.
228, No. 6, (2014), 631–648. 
19. Montazeri-Gh, M., Poursamad, A., and Ghalichi, B. “Application
of genetic algorithm for optimization of control strategy in
parallel hybrid electric vehicles,” Journal of the Franklin
Institute, Vol. 343, No. 4, (2006), 420–435. 
20. Montazeri-Gh, M. and Poursamad, A. “Application of genetic
algorithm for simultaneous optimisation of HEV component
sizing and control strategy,” International Journal of Alternative
Propulsion, Vol. 1, No. 1, (2006), 63–78. 
21. Long, V. T. and Nhan, N. V. “Bees-algorithm-based optimization
of component size and control strategy parameters for parallel
hybrid electric vehicles,” International Journal of Automotive
Technology, Vol. 13, No. 7, (2012), 1177–1183. 
22. Dorri, M. and Shamekhi, A. H. “Design and optimization of a new
control strategy in a parallel hybrid electric vehicle in order to
improve fuel economy,” Proceedings of the Institution of 
Mechanical Engineers, Part D: Journal of Automobile
Engineering, Vol. 225, No. 6, (2011), 747–759. 
23. Wang, Z., Huang, B., Xu, Y. and Li, W. “Optimization of Series
Hybrid Electric Vehicle Operational Parameters by Simulated
Annealing Algorithm,” In IEEE International Conference on
Control and Automation, (2007), 1536–1541. 
24. Delkhosh, M., Saadat Foumani, M. and Rostami, P. “Optimization
of powertrain and control strategy of hybrid electric vehicle,”
Scientia Iranica, Vol. 22, No. 5, (2015), 1842–1854. 
25. Basma, H., Halaby, H., Radwan, A. B. and Mansour, C. “Design of
optimal rule-based controller for plug-in series hybrid electric
vehicle,” In the 32nd International Conference on Efficiency,
Cost, Optimization, Simulation and Environmental Impact of
Energy Systems, Poland, (2019). 
26. Delkhosh, M., Saadat Foumani, M., Azad, N. L. and Rostami, P. “A
new control strategy for hybrid electric vehicles equipped with
continuously variable transmission,” In Proceedings of the
Institution of Mechanical Engineers, Part D: Journal of
Automobile Engineering, (2015), 1–14. 
 
 
27. Luus, R., Iterative Dynamic Programming. CRC Press, (2000).
28. Boukehili, A., Zhang, Y. T., Zhao, Q., Ni, C. Q., Su, H. F. and 
Huang, G. J. “Hybrid vehicle power management modeling and
refinement,” International Journal of Automotive Technology,
Vol. 13, No. 6, (2012), 987–998. 
29. Saadat Foumani, Mahmoud. "Multi-objective optimization of
hybrid electric vehicle equipped with power-split continuously
variable transmission." International Journal of Engineering,
Transactions C: Aspects, Vol. 29, No. 3 (2016), 368-377. 
30. Delkhosh, M., Foumani, M.S. and Azad, N.L., A New Framework
for Advancement of Power Management Strategies in Hybrid
Electric Vehicles. (2003). 
31. Saadat Foumani, Mahmoud. "Multi-objective optimization of
hybrid electric vehicle equipped with power-split continuously
variable transmission." International Journal of Engineering,
Transaction C: Aspects, Vol. 29, No. 3, (2016), 368-377. 
32. Delkhosh, M. and Saadat Foumani, M. “Multi-objective
geometrical optimization of full toroidal CVT,” International
Journal of Automotive Technology, Vol. 14, No. 5, (2013), 707–
715. 
33. Delkhosh, M. and Saadat Foumani, M. “Optimisation of fulltoroidal
continuously
variable
transmission in conjunction with
fixed ratio mechanism using particle swarm optimisation,”
Vehicle System Dynamics, Vol. 51, No. 5, (2013), 671–683. 
34. Civicioglu, P. “Backtracking Search Optimization Algorithm for
numerical optimization problems,” Applied Mathematics and
Computation, Vol. 219, No. 15, (2013), 8121–8144. 
35. Shimizu, K. and Seimiya, S. “Test procedure to evaluate fuel
consumption of HEVs-Universal procedure to secure accuracy,”
In 18th Electric Vehicle Symposium, Berlin, Germany, (2001).