Li-Ion Battery Management System for Electric Vehicles - A Practical Guide

被引:0
作者
Deng, Jing [1 ]
Li, Kang [1 ]
Laverty, David [1 ]
Deng, Weihua [2 ]
Xue, Yusheng [3 ]
机构
[1] Queens Univ Belfast, Sch Elect Elect Engn & Comp Sci, Belfast BT9 5AH, Antrim, North Ireland
[2] Shanghai Univ Elect Power, Elect Power Engn, Shanghai 200090, Peoples R China
[3] State Grid Elect Power Res Inst, Nanjing 210003, Jiangsu, Peoples R China
来源
INTELLIGENT COMPUTING IN SMART GRID AND ELECTRICAL VEHICLES | 2014年 / 463卷
关键词
Lithium-ion Electric vehicle; battery management system; intelligent charging; battery modelling; STATE-OF-CHARGE; ENERGY; PACKS;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Electric vehicles (EVs) are becoming more popular and have gained better customer acceptance in the past few years due to the improved performances, such as high acceleration rate and long driving distance from a single charging. Recent research also shows some promising benefits from integrating EVs with power grid. One of these is to use EV batteries as distributed energy storage. As a result, the excessive electricity generated from renewable resources can be stored in EVs and release to the power grid when needed. However, compared to traditional Nickel-cadmium and lead-acid batteries, Li-ion battery only can be operated in a narrow window, and needs to be properly monitored, managed and protected. This issue becomes severe when it is deployed for large applications, such as EVs and centralised electricity storage, where a large number of Li-Ion cells are interconnected to provide sufficient voltage and current. The solution mainly relies on a robust and efficient battery management system (BMS). This paper presents a brief review on the features of BMS, followed by a practical guide on selecting a commercial BMS from the market and designing a custom BMS for better control of functionalities. A Lithimate Pro BMS from Elithion is used to demonstrate the effectiveness of BMS in managing and protecting Li-Ion cells during the charge and discharge phases.
引用
收藏
页码:32 / 44
页数:13
相关论文
共 19 条
  • [1] [Anonymous], 2010, Battery Management Systems for Large Lithium Ion Battery Packs
  • [2] Cai CH, 2003, IEEE INT CONF FUZZY, P1068
  • [3] State-of-Charge Estimation for Lithium-Ion Batteries Using Neural Networks and EKF
    Charkhgard, Mohammad
    Farrokhi, Mohammad
    [J]. IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, 2010, 57 (12) : 4178 - 4187
  • [4] Online estimation of internal resistance and open-circuit voltage of lithium-ion batteries in electric vehicles
    Chiang, Yi-Hsien
    Sean, Wu-Yang
    Ke, Jia-Cheng
    [J]. JOURNAL OF POWER SOURCES, 2011, 196 (08) : 3921 - 3932
  • [5] Department of Energy and Climate Change, 2013, UK GREENH GAS EM PRO
  • [6] State-of-Charge Estimation of the Lithium-Ion Battery Using an Adaptive Extended Kalman Filter Based on an Improved Thevenin Model
    He, Hongwen
    Xiong, Rui
    Zhang, Xiaowei
    Sun, Fengchun
    Fan, JinXin
    [J]. IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, 2011, 60 (04) : 1461 - 1469
  • [7] Electric vehicles as a new power source for electric utilities
    Kempton, W
    Letendre, SE
    [J]. TRANSPORTATION RESEARCH PART D-TRANSPORT AND ENVIRONMENT, 1997, 2 (03) : 157 - 175
  • [8] State-of-charge and capacity estimation of lithium-ion battery using a new open-circuit voltage versus state-of-charge
    Lee, Seongjun
    Kim, Jonghoon
    Lee, Jaemoon
    Cho, B. H.
    [J]. JOURNAL OF POWER SOURCES, 2008, 185 (02) : 1367 - 1373
  • [9] A review on the key issues for lithium-ion battery management in electric vehicles
    Lu, Languang
    Han, Xuebing
    Li, Jianqiu
    Hua, Jianfeng
    Ouyang, Minggao
    [J]. JOURNAL OF POWER SOURCES, 2013, 226 : 272 - 288
  • [10] Integration of renewable energy into the transport and electricity sectors through V2G
    Lund, Henrik
    Kempton, Willett
    [J]. ENERGY POLICY, 2008, 36 (09) : 3578 - 3587