电源学报

基于修正安时积分法的锂离子电池荷电状态估算

PDF下载

梁叶中国电源学会学生会员 ¹ , 蔡孟冶 ¹ , 姜岩峰 ¹ , 王会刚 ²

电源学报 | 新能源发电与储能 2026,24(8): 131-139

收起

电源学报 |新能源发电与储能 2026 , 24 (8) : 131 -139

基于修正安时积分法的锂离子电池荷电状态估算

全屏

梁叶中国电源学会学生会员¹, 蔡孟冶¹, 姜岩峰¹, 王会刚²

作者信息

^1.江南大学集成电路学院，江阴　214442

^2.无锡华润微电子有限公司先进技术研究院，无锡　214061

通讯作者:

蔡孟冶（1988—　），男，通信作者，博士，副教授。研究方向：CMOS模拟与射频集成电路，可植入/穿戴式生物传感SoC芯片，超低功耗收发机芯片。E-mail：caimengye@jiangnan.edu.cn。

作者简介:

梁叶（1994—　），男，中国电源学会学生会员，硕士研究生。研究方向：锂离子电池BMS硬件设计，锂离子电池特性研究及SOC算法研究。E-mail：wxliangye@163.com。

姜岩峰（1972—　），男，博士，教授。研究方向：新型集成电路设计，新型半导体器件设计，新型磁性材料和磁性器件。E-mail：jiangyf@jiangnan.edu.cn。

王会刚（1974—　），男，硕士，高级工程师。研究方向：锂离子电池BMS系统设计及SOC算法研究。E-mail：wanghg@semi.crmicro.com。

State-of-charge Estimation of Lithium-ion Battery Based on Modified Ampere-hour Integral Method

Ye LIANG Student Member, CPSS¹, Mengye CAI¹, Yanfeng JIANG¹, Huigang WANG²

Affiliations

^1.School of Integrated Circuits, Jiangnan University, Jiangyin 214442, China

^2.Advanced Technology Research Institute, Wuxi China Resources Microelectronics Co., Ltd., Wuxi 214061, China

出版时间: 2026-08-30 doi: 10.13234/j.issn.2095-2805.2026.8.131

文章导航

摘要

收起

锂离子电池的荷电状态SOC（state-of-charge）是反映该电池剩余电量状态的重要参数。针对安时积分法SOC初值无法确定、累积误差逐渐变大的问题，提出一种修正安时积分法误差的算法。通过研究磷酸铁锂电池的充放电特性，得到开路电压-荷电状态OCV-SOC（open circuit voltage-SOC）曲线及直流内阻-端电压曲线。所提算法在锂离子电池充电状态下，电量达到判饱条件时进行校准；放电状态下，电量为7%时基于电池特性曲线在线校准误差。试验结果显示，所提算法在SOC估算的过程中可以有效减小误差，并将误差控制在2.00%以内，具有较高的估算精度。

关键词

锂离子电池 / 荷电状态 / 安时积分法 / 电池管理系统 / 误差修正

Abstract

收起

The state-of-charge (SOC) of a lithium-ion battery is an important parameter that reflects the state of its remaining energy. To address the issues of the initial SOC being indeterminate and the cumulative error increasing over time in the ampere-hour integral method, an algorithm is proposed to correct the error in the ampere-hour integral method. Through the study of the charge and discharge characteristics of a lithium-ion iron phosphate battery, the open circuit voltage-SOC (OCV-SOC) curve and the DC internal resistance-terminal voltage curve are obtained. The proposed algorithm calibrates the SOC when the battery reaches the full charge condition during charging, and it performs online error calibration based on the battery’s characteristic curves when the values of capacity are 7% in the discharge state respectively. The experimental results show that it can effectively reduce the error in the SOC estimation process and control it within 2.00%, indicating a high estimation accuracy.

Key words

Lithium-ion battery / state-of-charge (SOC) / ampere-hour integral method / battery management system (BMS) / error correction

引用本文

梁叶中国电源学会学生会员, 蔡孟冶, 姜岩峰, 王会刚. 基于修正安时积分法的锂离子电池荷电状态估算. 电源学报, 2026 , 24 (8) : 131 -139 . DOI: 10.13234/j.issn.2095-2805.2026.8.131

Ye LIANG, Mengye CAI, Yanfeng JIANG, Huigang WANG. State-of-charge Estimation of Lithium-ion Battery Based on Modified Ampere-hour Integral Method[J]. Journal of Power Supply, 2026 , 24 (8) : 131 -139 . DOI: 10.13234/j.issn.2095-2805.2026.8.131

基金

收起

国家重点研发计划资助项目(2024YFB4505400)

参考文献

收起

文献

收起

参考文献引证文献

排序方式：

[1]

董春伟, 苏志江, 潘广宏, 等. 全固态锂硫电池研究进展与展望[J]. 电源技术, 2026, 50(4): 593-600. Dong Chunwei, Su Zhijiang, Pan Guanghong, et al. Research progress and prospects of all-solid-state Li-S batteries[J]. Chinese Journal of Power Sources, 2026, 50(4): 593-600. (in Chinese)

[2]

Wu Longxing, Lü Zhiqiang, Huang Zebo, et al. Physics-based battery SOC estimation methods: Recent advances and future perspectives[J]. Journal of Energy Chemistry, 2024, 89: 27-40.

[3]

Ng K S, Moo C S, Chen Yiping, et al. Enhanced coulomb counting method for estimating state-of-charge and state-of-health of lithium-ion batteries[J]. Applied Energy, 2009, 86(9): 1506-1511.

[4]

申彩英, 左凯. 基于开路电压法的磷酸铁锂电池SOC估算研究[J]. 电源技术, 2019, 43(11): 1789-1791. Shen Caiying, Zuo Kai. Research on SOC estimation of LiFePO₄ batteries based on open circuit voltage method[J]. Chinese Journal of Power Sources, 2019, 43(11): 1789-1791. (in Chinese)

[5]

Tan Xiaojun, Tan Yuqing, Zhan Di, et al. Real-time state-of-health estimation of lithium-ion batteries based on the equivalent internal resistance[J]. IEEE Access, 2020, 8: 56811-56822.

[6]

成燕, 郑林弘, 刘江. 基于模态分解和时间序列的锂电池健康状态估计[J]. 电源学报, 2025, 23(5): 241-250. Chen Yan, Zheng Linhong, Liu Jiang. Estimation of state-of-health of lithium-ion batteries based on modal decomposition and time series[J]. Journal of Power Supply, 2025, 23(5): 241-250. (in Chinese)

[7]

许傲然, 戴菁, 谷彩莲, 等. 基于WOA优化扩展卡尔曼算法的锂离子电池SOC估算研究[J]. 电源学报, 2025, 23(2): 232-239. Xu Aoran, Dai Jing, Gu Cailian, et al. Research on SOC estimation of lithium-ion battery based on WOA optimized extended Kalman algorithm[J]. Journal of Power Supply, 2025, 23(2): 232-239. (in Chinese)

[8]

汪伟, 黄河, 龙宇舟, 等. 基于改进安时积分法的动力电池SOC估算[J]. 客车技术与研究, 2021, 43(3): 12-14. Wang Wei, Huang He, Long Yuzhou, et al. SOC estimation of power battery based on improved ampere-hour integration method[J]. Bus & Coach Technology and Research, 2021, 43(3): 12-14. (in Chinese)

[9]

Bavand A, Ali Khajehoddin S, Ardakani M, et al. Online estimations of Li-ion battery SOC and SOH applicable to partial charge/discharge[J]. IEEE Transactions on Transportation Electrification, 2022, 8(3): 3673-3685.

[10]

Bao Yun, Dong Wenbin, Wang Dian. Online internal resistance measurement application in lithium ion battery capacity and state of charge estimation[J]. Energies, 2018, 11(5): 1073.

[11]

贠祥, 张鑫, 王超, 范兴明. 基于联合参数辨识的粒子群优化扩展粒子滤波的锂电池荷电状态估计[J]. 电工技术学报, 2024, 39(2): 595-606. Yun Xiang, Zhang Xin, Wang Chao, Fan Xingming. State of charge estimation of Li-ion battery using particle swarm optimization extended Kalman particle filter based on joint parameter identification[J]. Transactions of China Electrotechnical Society, 2024, 39(2): 595-606. (in Chinese)

[12]

刘旖琦, 雷万钧, 刘茜, 等. 基于双自适应扩展粒子滤波器的锂离子电池状态联合估计[J]. 电工技术学报, 2024, 39(2): 607-616. Liu Yiqi, Lei Wanjun, Liu Qian, et al. Joint state estimation of lithium-ion battery based on dual adaptive extended particle filter[J]. Transactions of China Electrotechnical Society, 2024, 39(2): 607-616. (in Chinese)

[13]

Yu Quanqing, Xiong Rui, Lin Cheng, et al. Lithium-ion battery parameters and state-of-charge joint estimation based on H-infinity and unscented Kalman filters[J]. IEEE Transactions on Vehicular Technology, 2017, 66(10): 8693-8701.

[14]

Huang Chao, Wang Zhenhua, Zhao Zihan, et al. Robustness evaluation of extended and unscented Kalman filter for battery state of charge estimation[J]. IEEE Access, 2018, 6: 27617-27628.

[15]

Shu Xing, Li Guang, Shen Jiangwei, et al. An adaptive fusion estimation algorithm for state of charge of lithiumion batteries considering wide operating temperature and degradation[J]. Journal of Power Sources, 2020, 462: 228132.

[16]

Li Weihan, Cao Decheng, Jöst D, et al. Parameter sensitivity analysis of electrochemical model-based battery management systems for lithium-ion batteries[J]. Applied Energy, 2020, 269: 115104.

[17]

Ramadesigan V, Chen Kejia, Burns N A, et al. Parameter estimation and capacity fade analysis of lithium-ion batteries using reformulated models[J]. Journal of the Electrochemical Society, 2011, 158(9): A1048.

[18]

刘伯峥, 孙馨怡, 董世佳, 等. 磷酸铁锂电池开路电压曲线特性分析[J]. 能源研究与管理, 2023, 15(1): 95-101. Liu Bozheng, Sun Xinyi, Dong Shijia, et al. Characteristic analysis of open circuit voltage curve of LiFePO₄ battery[J]. Energy Research and Management, 2023, 15(1): 95-101. (in Chinese)

[19]

Hu Xiaosong, Li Shengbo, Peng Huei. A comparative study of equivalent circuit models for Li-ion batteries[J]. Journal of Power Sources, 2012, 198: 359-367.

[20]

陈贵升, 许杨松, 沈颖刚, 等. 基于OCV模型优化的磷酸铁锂电池SOC估计[J]. 电源技术, 2024, 48(7): 1281-1288. Chen Guisheng, Xu Yangsong, Shen Yinggang, et al. SOC estimation of LiFePO₄ battery based on OCV model optimization[J]. Chinese Journal of Power Sources, 2024, 48(7): 1281-1288. (in Chinese)

[21]

刘志聪, 张彦会. 锂离子电池参数辨识及荷电状态的估算[J]. 储能科学与技术, 2022, 11(11): 3613-3622. Liu Zhicong, Zhang Yanhui. Parameter identification and state of charge estimation of lithium-ion batteries[J]. Energy Storage Science and Technology, 2022, 11(11): 3613-3622. (in Chinese)

[22]

刘璇, 王立欣, 吕超, 等. 锂离子电池建模与参数识别[J]. 电源学报, 2018, 16(1): 145-150. Liu Xuan, Wang Lixin, Lü Chao, et al. Modeling and parameter identification for lithium-ion battery[J]. Journal of Power Supply, 2018, 16(1): 145-150. (in Chinese)

[23]

鲁文凡, 吕帅帅, 李志扬, 等. 电动汽车用磷酸铁锂动力电池内阻特性研究[J]. 化工新型材料, 2018, 46(1): 175-177. Lu Wenfan, Lü Shuaishuai, Li Zhiyang, et al. Characteristic study on internal resistance of LiFePO₄ power battery for EV[J]. New Chemical Materials, 2018, 46(1): 175-177. (in Chinese)

[24]

卢艳华. 车用三元锂离子动力电池内阻特性分析[J]. 电源技术, 2017, 41(5): 702-704. Lu Yanhua. Impedance characteristics of lithium ion power battery with NCM cathode for electric vehicles[J]. Chinese Journal of Power Sources, 2017, 41(5): 702-704. (in Chinese)

[25]

刘锐, 尚丽平, 屈薇薇. 低温条件下锂电池放电特性分析[J]. 电源学报, 2024, 22(S1): 98-104. Liu Rui, Shang Liping, Qu Weiwei. Analysis of discharge characteristics of lithium batteries at low temperatures[J]. Journal of Power Supply, 2024, 22(S1): 98-104. (in Chinese)

2026年第24卷第8期

PDF下载

引用本文

BibTeX

文章信息

doi: 10.13234/j.issn.2095-2805.2026.8.131

接收时间：2024-11-15
首发时间：2026-10-29
出版时间：2026-08-30

补充材料

相关文章

文章信息

作者

出版历史

收稿日期：2024-11-15
修回日期：2024-12-30
录用日期：2025-01-21

基金

National Key Research and Development Program of China(2024YFB4505400)

国家重点研发计划资助项目(2024YFB4505400)

作者信息

^1.江南大学集成电路学院，江阴　214442

^2.无锡华润微电子有限公司先进技术研究院，无锡　214061

通讯作者:

参考文献

分享链接

https://castjournals.cast.org.cn/joweb/dyxb/CN/10.13234/j.issn.2095-2805.2026.8.131

分享至

全文二维码

扫描看全文

引用本文

BibTeX

本文的引用情况

2种不同金属材料的力学参数

科 Family	属数 Number of genus	种数 Number of species	占总种数比例 Percentage of total species (%)	属 Genus	种数 Number of species	占总种数比例 Percentage of total species (%)
鹅膏菌科Amanitaceae	2	11	5.26	鹅膏菌属 Amanita	10	4.78
小菇科 Mycenaceae	2	12	5.74	丝盖伞属 Inocybe	5	2.39
多孔菌科 Polyporaceae	8	14	6.70	蜡蘑属 Laccaria	5	2.39
红菇科 Russulaceae	3	23	11.00	小皮伞属 Marasmius	6	2.87
				小菇属 Mycena	11	5.26
				光柄菇属 Pluteus	5	2.39
				红菇属 Russula	17	8.13
				栓菌属 Trametes	5	2.39

关闭全屏

BibTeX
EndNote
RefWorks
TxT