A review of state of health and remaining useful life estimation methods for lithium-ion battery in electric vehicles: Challenges and recommendations

被引：482

作者：

Lipu, M. S. Hossain ^{[1
,2
]}

Hannan, M. A. ^{[3
]}

Hussain, Aini ^{[1
]}

Hoque, M. M. ^{[4
]}

Ker, Pin J. ^{[3
]}

Saad, M. H. M. ^{[1
]}

Ayob, Afida ^{[1
]}

机构：

[1] Univ Kebangsaan Malaysia, Ctr Integrated Syst Engn & Adv Technol Integra, Fac Engn & Built Environm, Bangi 43600, Selangor, Malaysia

[2] Univ Asia Pacific, Dept Elect & Elect Engn, Dhaka 1215, Bangladesh

[3] Univ Tenaga Nas, Dept Elect Power Engn, Kajang 43000, Selangor, Malaysia

[4] Univ Chittagong, Dept Elect & Elect Engn, Chittagong 4331, Bangladesh

来源：

JOURNAL OF CLEANER PRODUCTION | 2018年 / 205卷

关键词：

Lithium-ion battery; Electric vehicle; State of health; Remaining useful life; Thermal runway; Aging; Safety and protection; Environmental impact; ENERGY MANAGEMENT-SYSTEM; CHARGE ESTIMATION; PARTICLE FILTER; NEURAL-NETWORK; AGING MECHANISMS; STORAGE SYSTEMS; SOH ESTIMATION; KALMAN FILTER; CYCLE-LIFE; MODEL;

D O I：

10.1016/j.jclepro.2018.09.065

中图分类号：

X [环境科学、安全科学];

学科分类号：

08 ; 0830 ;

摘要：

Electric vehicles (EVs) have become increasingly popular due to zero carbon emission, reduction of fossil fuel reserve, comfortable and light transport. However, EVs employing lithium-ion battery are facing difficulties in terms of predicting accurate health and remaining useful life states due to various internal and external factors. Currently, very few papers are addressed to summarize the state of health (SOH) and remaining useful life (RUL) estimation approaches. In this regard, the goal of this paper is to comprehensively review the different estimation models to predict SOH, and RUL in a comparative manner. The results identify the classifications, characteristics and evaluation processes with advantages and disadvantages for EV applications. The review also investigates the issues and challenges with possible solutions. Furthermore, the review provides some selective proposals for the further technological development of SOH, and RUL estimation for lithium-ion batteries. All the highlights insight this review will hopefully lead to the increasing efforts towards the development of the advanced SOH and RUL methods for future EV uses. (C) 2018 Elsevier Ltd. All rights reserved.

引用

页码：115 / 133

页数：19

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