Parameters optimum matching of pure electric vehicle dual-mode coupling drive system
详细信息 查看全文
- 作者：LiPeng Zhang (1) (2)
Liang Li (1)
BingNan Qi (2)
Chong Wang (2)
YaHui Zhang (1)
Jian Song (1) - 关键词：pure electric vehicle ; dual ; mode coupling drive system ; parameter optimum matching ; genetic algorithm
- 刊名：SCIENCE CHINA Technological Sciences
- 出版年：2014
- 出版时间：November 2014
- 年：2014
- 卷：57
- 期：11
- 页码：2265-2277
- 全文大小：2,509 KB
- 参考文献：1. Zhu H, Li L, Jin M, et al. Real-time yaw rate prediction based on a non-linear model and feedback compensation for vehicle dynamics control. Proc I Mech E Part D: J Aut, 2013, 227: 1431鈥?445 CrossRef
2. Murata S. Innovation by in-wheel-motor drive unit. Vehicle Syst Dyn, 2012, 50: 807鈥?30 CrossRef
3. Dadashnialehi A, Bab-Hadiashar A, Cao Z W, et al. Intelligent sensorless ABS for in-wheel electric vehicles. IEEE T Ind Electron, 2014, 61: 1957鈥?969 CrossRef
4. Hori Y. Future vehicle driven by electricity and control-research on 4 wheels motored 鈥淯OT March II鈥? IEEE T Ind Electron, 2004, 51: 954鈥?6 CrossRef
5. Wang J N, Wang Q N, Jin L Q, et al. Independent wheel torque control of 4WD electric vehicle for differential drive assisted steering. Mechatronics, 2011, 21: 63鈥?6 CrossRef
6. Zhao W Z, Xu X H, Wang C Y. Multidiscipline collaborative optimization of differential steering system of electric vehicle with motorized wheels. Sci China Tech Sci, 2012, 55: 3462鈥?468 CrossRef
7. Xiong L, Yu Z P, Wang Y, et al. Vehicle dynamics control of four in wheel motor drive electric vehicle using gain scheduling based on tyre cornering stiffness estimation. Vehicle Syst Dyn, 2012, 50: 831鈥?46 CrossRef
8. Wang R R, Wang J M. Fault-tolerant control with active fault diagnosis for four-wheel independently driven electric ground vehicles. IEEE T Veh Technol, 2011, 60: 4276鈥?287 CrossRef
9. Chu W B, Luo Y G, Han Y W, et al. Rule-based traction system failure control of distributed electric drive vehicle. J Mech Eng, 2012, 48: 90鈥?5, 102 CrossRef
10. Mutoh N, Nakano Y. Dynamics of front-and-rear-wheel-independent-drive-type electric vehicles at the time of failure. IEEE T Ind Electron, 2012, 59: 1488鈥?499 CrossRef
11. Zhang L P, Lin C, Qi B N. Mechanism and design of EV changing modes propulsion system. In: Bilof R, eds. International Conference on Measuring Technology and Mechatronics Automation, Zhangjiajie, China, 2009. 91鈥?4
12. Zhang L P, Qi B N, Lin C. Torque behavior of electric vehicle change mode drive system. In: Guerrero J E, ed. International Conference on Computing, Control and Industrial Engineering, Wuhan, China, 2010. 87鈥?0
13. Nagaya G, Wakao Y, Abe A. Development of an in-wheel drive with advanced dynamic-damper mechanism. JSAE Review, 2003, 24: 477鈥?81 CrossRef
14. Yang C, Jiao X H, Li L, et al. Electromechanical coupling drive control for single-shaft parallel hybrid powertrain. Sci China Tech Sci, 2014, 57: 541鈥?49 CrossRef
15. Yu Z S. Theory of Automobile. Beijing: Machinery Industry Press, 2009. 75
16. Chiasson J, Vairamohan B. Estimating the state of charge of a battery. IEEE T Cont Syst T, 2005, 13: 465鈥?70 CrossRef
17. Goldberg D E, Holland J H. Genetic Algorithms and Machine Learning, Machine Learning 3. Dordrecht: Kluwer Academic Publishers, 1988. 95鈥?9
18. Zhao W Z, Wang C Y. Mixed H2/H鈭?/sub> road feel control of EPS based on genetic algorithm. Sci China Tech Sci, 2012, 55: 72鈥?0 CrossRef
19. Leung Y W, Wang Y P. An orthogonal genetic algorithm with quantization for global numerical optimization. IEEE T Evol Comput, 2001, 5: 41鈥?3 CrossRef
20. Sadjadi F A. Comparison of fitness scaling functions in genetic algorithms with applications to optical processing. Proc SPIE, 2004, 5557: 356鈥?64 CrossRef
21. Montazeri-Gh M, Poursamad A, Ghalichi B. Application of genetic algorithm for optimization of control strategy in parallel hybrid electric vehicles. J Franklin Institute, 2006, 343: 420鈥?35 CrossRef
22. Nada M, Al-Salami A. Ant colony optimization algorithm. UbiCC J, 2009, 4: 823鈥?26 - 作者单位：LiPeng Zhang (1) (2)
Liang Li (1)
BingNan Qi (2)
Chong Wang (2)
YaHui Zhang (1)
Jian Song (1)
1. State Key Laboratory of Automotive Safety and Energy, Tsinghua University, Beijing, 100084, China
2. School of Mechanical and Automotive Engineering, Liaocheng University, Liaocheng, 252059, China - ISSN：1869-1900
文摘
As an important development direction of pure electric vehicle drive system, the distributed drive system has the advantages of compact structure, high transmission efficiency, and flexible control, but there are some serious problems such as high performance requirements to the drive motors, complex control strategies, and poor reliability. To solve these problems, a two motors dual-mode coupling drive system has been developed at first, which not only has the capacity of two-speed gear shifting, but also can automatically switch between the distributed drive and the centralized drive by means of modes change control. So, the performance requirements to the drive motors can be reduced, the problem of abnormal running caused by the fault of unilateral distributed drive systems also can be resolved by replacing the drive mode with centralized drive. Then, the system parameters primary and the optimum matching under the principle of efficiency optimization have been carried out, which makes the drive system achieve predetermined functions and meet the actual demands of different operating statuses. At last, the economic comparison of a pure electric vehicle installation with a dual-mode coupling drive system, a single-motor centralized drive system or a dual-motor distributed drive system in the simulation conditions has been completed. Compared with other systems, the driving range of the electric vehicle driven by the designed system is significantly increased, which proves the better efficiency and application value of the system.