• CN: 11-2187/TH
  • ISSN: 0577-6686

Journal of Mechanical Engineering ›› 2017, Vol. 53 ›› Issue (16): 20-31.doi: 10.3901/JME.2017.16.020

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Review of Modeling Techniques for Lithium-ion Traction Batteries in Electric Vehicles

HU Xiaosong1,2, TANG Xiaolin1,2   

  1. 1. State Key Laboratory of Mechanical Transmission, Chongqing University, Chongqing 400044;
    2. Department of Automotive Engineering, Chongqing University, Chongqing 400044
  • Received:2016-08-25 Revised:2017-07-15 Online:2017-08-20 Published:2017-08-20

Abstract: Electric vehicles(EVs) are significant ingredients of sustainable transportation system. Traction battery technology, however, is a key bottleneck currently thwarting the rapid development of EVs, which directly makes the general public concern over driving range, recharge time, and safety of EVs. In order to ensure high-efficiency, safe, and reliable operations of traction batteries in complicated vehicular environment, advanced battery management systems are crucial. Since present sensing technologies cannot directly probe key microscopic physical variables inside batteries, how to establish high-fidelity battery models constitutes a heavy challenge for developing battery management systems, substantially affecting the effectiveness and resilience of battery management. Categories of vehicular traction batteries are first briefed, as well as their comparative outcomes, showcasing the superiority of lithium-ion battery. Standard functionalities of lithium-ion battery management system are then introduced, highlighting the great significance and importance of battery modeling. From four perspectives of electrical model, thermal model, electro-thermal model, and aging model, existing modeling approaches in the open literature are systematically surveyed. Moreover, diverse methods are categorized well. Novel control-oriented model topologies and modeling ideas are emphasized, with the aim to catalyze the development of advanced model-based battery management algorithms.

Key words: battery management, clean-energy vehicle, Li-ion battery, modeling, sustainable transportation

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