Li-Ion Battery Performance Degradation Modeling for the Optimal Design and Energy Management of Electrified Propulsion Systems

被引:32
|
作者
Chen, Li [1 ]
Tong, Yuqi [1 ,2 ]
Dong, Zuomin [1 ]
机构
[1] Univ Victoria, Inst Integrated Energy Syst, Dept Mech Engn, Victoria, BC V8W 2Y2, Canada
[2] State Assigned Elect Vehicle Power Battery Ctr, Beijing 100072, Peoples R China
关键词
li-ion battery; performance degradation modelling; electrified propulsion; battery sizing; powertrain optimization; optimal energy management; CAPACITY FADE; AGING MECHANISMS; CYCLE LIFE; PART I; CELLS; IDENTIFICATION; PREDICTION; CALENDAR;
D O I
10.3390/en13071629
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
Heavy-duty hybrid electric vehicles and marine vessels need a sizeable electric energy storage system (ESS). The size and energy management strategy (EMS) of the ESS affects the system performance, cost, emissions, and safety. Traditional power-demand-based and fuel-economy-driven ESS sizing and energy management has often led to shortened battery cycle life and higher replacement costs. To consider minimizing the total lifecycle cost (LCC) of hybrid electric propulsion systems, the battery performance degradation and the life prediction model is a critical element in the optimal design process. In this work, a new Li-ion battery (LIB) performance degradation model is introduced based on a large set of cycling experiment data on LiFePO4 (LFP) batteries to predict their capacity decay, resistance increase and the remaining cycle life under various use patterns. Critical parameters of the semi-empirical, amended equivalent circuit model were identified using least-square fitting. The model is used to calculate the investment, operation, replacement and recycling costs of the battery ESS over its lifetime. Validation of the model is made using battery cycling experimental data. The new LFP battery performance degradation model is used in optimizing the sizes of the key hybrid electric powertrain component of an electrified ferry ship with the minimum overall LCC. The optimization result presents a 12 percent improvement over the traditional power demand-driven hybrid powertrain design method. The research supports optimal sizing and EMS development of hybrid electric vehicles and vessels to achieve minimum lifecycle costs.
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页数:19
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