Control Strategy Optimization for Hybrid Electric Vehicle Based on Multi-Chaotic Operators Genetic Algorithm

Abstract

Abstract:

Abstract： This paper presented a fuzzy logic control strategy for a parallel HEV equipped with battery/ultra capacitor based hybrid energy storage system. By combining the population evolution feature of genetic algorithm and the randomicity and ergodicity of chaos sequence, the chaotic initialization, disturbance and local search operators were introduced into non-donminated sorting genetic algorithm-II(NSGA-II) to construct a novel multichaotic operators NSGA-II (MCO-NSGA-II). MCO-NSGA-II was adopted to optimize the fuzzy control strategy for improving the fuel economy and emission performance of the target HEV. The results demonstrate that chaotic initialization, disturbance operators can improve the searching ability of NSGA-II and increase the diversity of the solutions. The chaotic local search operator can further improve the local searching ability to obtain better pareto solutions. By adopting MCO-NSGA-II, the fuel consumption of HEV under ECE driving cycle is reduced by 11.8% while the HC, CO and NOx emissions of HEV are decreased by 7.72%, 15.72% and 11.77%.

Key words: chaotic operators, genetic algorithm, multi-objective optimization, hybrid electric vehicle

CLC Number:

U 469.72文

LIANG Junyi,ZHANG Jianlong,MA Xuerui,YIN Chengliang. Control Strategy Optimization for Hybrid Electric Vehicle Based on Multi-Chaotic Operators Genetic Algorithm[J]. Journal of Shanghai Jiaotong University, 2015, 49(04): 442-449.

References

［1］Ehsani M, Gao Y, Emadi A. Modern electric, hybrid electric, and fuel cell vehicles［M］. Boca Raton: CRC Press, 2009:12.

［2］Lee H D, Sul S K. Fuzzylogicbased torque control strategy for paralleltype hybrid electric vehicle［J］. IEEE Transactions on Industrial Electronics, 1998, 45(4): 625632.

［3］Xiong Weiwei, Zhang Yong, Yin Chengliang. Optimal energy management for a seriesparallel hybrid electric bus［J］. Energy Conversion and Management, 2009, 50(7): 17301738.

［4］Valerie H J, Keith B W, David J R. HEV control strategy for realtime optimization of fuel economy and emissions［J］. SAE Technical Paper, 2000, 2000011543.

［5］Zhang B, Chen Z, Mi C, et al. Multiobjective parameter optimization of a series hybrid electric vehicle using evolutionary algorithms［C］//Vehicle Power and Propulsion Conference 2009. Dearborn: IEEE, 2009:921925.

［6］Xiong Weiwei, Yin Chengliang, ZHANG Yong, et al. Seriesparallel hybrid vehicle control strategy design and optimization using realvalued genetic algorithm［J］. Chinese Journal of Mechanical Engineering, 2009, 22(6): 862868.

［7］张志英, 徐建祥,计峰.基于遗传算法的船舶分段堆场调度研究［J］.上海交通大学学报, 2013, 47(7): 10361042.

ZHANG Zhiying, XU Jianxiang, JI Feng. Shipbuilding yard scheduling approach based on genetic algorithm［J］. Journal of Shanghai Jiaotong University, 2013, 47(7): 10361042.

［8］陶猛,王广玮.基于多目标遗传算法的吸声覆盖层参数优化设计［J］.上海交通大学学报, 2013, 47(8): 13001305.

TAO Meng, WANG Guangwei. Parameter optimization of a sound absorption layer based on multiobjective genetic algorithm［J］. Journal of Shanghai Jiaotong University, 2013, 47(8): 13001305.

［9］Deb K, Pratap A, Agarwal S, et al.A fast and elitist multiobjective genetic algorithm: NSGAII［J］. IEEE Transactions on Evolutionary Computation, 2002， 6(2): 182197.

［10］Guo D, Wang J, Huang J, et al. ChaoticNSGAII: An effective algorithm to solve multiobjective optimization problems［C］//2010 International Conference on Intelligent Computing and Integrated Systems (ICISS). Guilin, China: IEEE, 2010: 2023.

［11］Ren Bingqun, Zhong Weizhou. Multiobjective optimization using chaos based PSO［J］. Information Technology Journal, 2011, 10(10): 19081916.

［12］Guo Yiqiang, Wu Yanbin, Ju Zhengshan, et al. Remote sensing image classification by the Chaos Genetic Algorithm in monitoring land use changes［J］. Mathematical and Computer Modelling, 2010, 51(11): 14081416.

［13］Eslami M, Shareef H, Mohamed A. Power system stabilizer design using hybrid multiobjective particle swarm optimization with chaos［J］. Journal of Central South University of Technology, 2011, 18(5): 15791588.

［14］Liang Junyi, Zhang Jianlong, Zhang Xi, et al. Energy management strategy for a parallel hybrid electric vehicle equipped with a battery/ultracapacitor hybrid energy storage system［J］. Journal of Zhejiang University SCIENCE A, 2013, 14(8): 535553.

［15］May R M. Simple mathematical models with very complicated dynamics［J］. Nature, 1976, 261(5560): 459467.

［16］Zitzler E, Thiele L. Multiobjective evolutionary algorithms: A comparative case study and the strength pareto approach［J］. IEEE Transactions on Evolutionary Computation, 1999, 3(4): 257271.

［17］Schott J R. Fault tolerant design using single and multicriteria genetic algorithm optimization［D］. Cambridge MA: Massachusetts Institute of Technology, 1995.

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