锂离子动力电池SOC估算技术进展综述

Review of SOC Estimation Technology for Lithium-ion Power Batteries

本文回顾了电池管理系统(Battery Management System,BMS)在电动汽车和可再生能源领域的关键发展阶段,本文重点讨论了电池剩余能量监测技术,即荷电状态(State of Charge,SOC)估计方法。文章概述了常见的SOC测量方法,包括基于模型法、安时积分法、放电测试法和人工神经网络法等。随着技术和时代的发展,电池管理系统正朝着智能化方向演进,采用更为先进的控制方法以提升系统性能。结合新型互联网+的服务模式,云计算和大数据在BMS中的潜在应用也在快速发展,为BMS和SOC估算带来了新的可能性。从未来发展趋势来看新型电池技术和应用场景的不断发展,将对SOC估算技术提出更高要求。在电动汽车快速发展的大背景下,持续优化和创新电池估算方法以满足各类电池和应用环境的特定需求已成为行业发展的必然趋势。

This paper reviews the key development stages of Battery Management System(BMS)in the field of electric vehicles and renewable energy,and focuses on battery residual energy monitoring technology,that is,the State of Charge(SOC)estimation method.This article provides an overview of common SOC measurement methods,including model-based method,ampere-hour integration method,discharge test method,and artificial neural network method.With the development of technology and the times,battery management systems are evolving in the direction of intelligence,adopting more advanced control methods to improve system performance.Combined with the new Internet+service model,the potential application of cloud computing and big data in BMS is also developing rapidly,bringing new possibilities for BMS and SOC estimation.From the perspective of future development trends,the continuous development of new battery technologies and application scenarios will put forward higher requirements for SOC estimation technology.Under the background of the rapid development of electric vehicles,continuous optimization and innovation of battery estimation methods to meet the specific needs of various batteries and application environments has become an inevitable trend in the development of the industry.