吉林大学学报(工学版) ›› 2017, Vol. 47 ›› Issue (1): 8-14.doi: 10.13229/j.cnki.jdxbgxb201701002

• Orginal Article • Previous Articles     Next Articles

Energy management optimization of hybrid energy storage system (HESS) based on dynamic programming

SONG Chuan-xue, ZHOU Fang, XIAO Feng   

  1. State Key Laboratory of Automotive Simulation and Control,Jilin University,Changchun 130022,China
  • Received:2015-12-20 Online:2017-01-20 Published:2017-01-20

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Abstract: A multi-objective optimization method aiming at minimizing HESS energy consumption and battery capacity loss is proposed. The battery loss is considered as a state variable, then, the multi-objective optimization problem is transformed into single objective with two state variables. The optimization problem is solved using dynamic programming algorithm, thus obtaining the Pareto-optimal sets. The optimization result is analyzed and a series of control rules are acquired, then, based on these rules, a rule-based power slitting strategy is proposed. Finally, the proposed strategy is simulated under Urban Dynamometer Driving Schedule condition. Results show that, compared with dynamic programming results, HESS energy consumption increases by 1%, and battery capacity loss increases by 0.4%, similar effect with dynamic programming is achieved. This proposed online ene4gy management is sub-optimal on both targets.

Key words: vehicle engineering, hybrid energy storage system, energy management, multi-objective dynamic programming, capacity losses

CLC Number: 

  • U461.8
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