Abstract
A torque distribution strategy was designed by using fuzzy logic to realize the optimal control. The vehicle load zones were dynamically divided into several zones by several torque lines to indicate the drivers demand and the high or low efficient operating areas of the diesel engine. The fuzzy logic controller with trapezoid membership function and Mamdani rule reference mechanism was utilized. There are over 100 rules used in this fuzzy-based torque distribution strategy which are sorted into four rule-bases. The fuel economy and acceleration tests were designed to test and validate the integrated starter/generator (ISG) bus performance using fuzzy-based torque distribution strategy. The fuel economy is improved 7.7% compared with the rule-based strategy. Finally the road test results reveal that there is about 15% improvement of fuel economy. And the 0–50 km/h acceleration time is 9.5% shorter than the original bus.
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References
Chan C C. The state of the art of electric and hybrid vehicles [J]. Proc IEEE, 2002, 90: 247–275.
Demirdoven N, Deutch J. Hybrid cars now, fuel cell cars later [J]. Science, 2004, 305: 974–976.
Zadeh A G, Fahim A, El-Gindy M. Neural network and fuzzy logic applications to vehicle systems: Literature survey [J]. International Journal of Vehicle Design, 1997, 18: 132–193.
Schouten N J, Salman M A, Kheir N A, et al. Energy management strategies for parallel hybrid vehicles using fuzzy logic [J]. Control Engineering Practice, 2003, 11: 171–177.
Kheir N A, Salman M A, Schouten N J, et al. Emissions and fuel economy trade-off for hybrid vehicles using fuzzy logic [J]. Mathematics and Computers in Simulation, 2004, 66: 155–172.
Langari R, Won J-S. Intelligent energy management agent for a parallel hybrid vehicle — Part I: System architecture and design of the driving situation identification process [J]. IEEE Transactions on Vehicular Technology, 2005, 54: 925–934.
Won J-S, Langari R. Intelligent energy management agent for a parallel hybrid vehicle — Part II: Torque distribution, charge sustenance strategies, and performance results [J]. IEEE Transactions on Vehicular Technology, 2005, 54: 935–953.
Baumann B M, Washington G, Glenn B C, et al. Mechatronic design and control of hybrid electric vehicles [J]. IEEE/ASME Transactions on Mechatronics, 2000, 5: 58–72.
YIN C L, Pu J H, Zhang J W, et al. Fuzzy torque control strategy for Parallel hybrid electric vehicles [J]. International Journal of Automotive Technology, 2005, 6: 592–536.
YIN C L, Pu J H, Zhang J W, et al. The fuzzy torque control strategy for parallel hybrid electric vehicles [J]. Journal of Shanghai Jiaotong University, 2006, 40(1): 157–162 (in Chinese).
Zhang J, Tong Y, OUYANG M G, et al. Torque management strategy for hybrid electric vehicles [J]. Journal of Tsinghua University (Sci & Tech), 2003, 43: 1134–1142 (in Chinese).
Zhong H, Ao G Q, Qiang J X, et al. The development of a real-time hardware-in-the-loop test bench for hybrid electric vehicle based on multi-thread technology [C]//IEEE International Conference on Vehicular Electronics and Safety. Shanghai, China: IEEE, 2006: 470–476.
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Zhong, H., Ao, Gq., Wang, F. et al. Torque distribution strategy for integrated starter/ generator hybrid bus implemented by fuzzy algorithm. J. Shanghai Jiaotong Univ. (Sci.) 13, 323–329 (2008). https://doi.org/10.1007/s12204-008-0323-1
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DOI: https://doi.org/10.1007/s12204-008-0323-1
Key words
- hybrid electric vehicle
- integrated starter/generator (ISG)
- torque distribution strategy
- fuzzy logic control