汽车电池管理系统的智能化控制与能效优化

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中图分类号：U463.633 文献标识码：A 文章编号：1003-8639(2025)07-0001-03

IntelligentControl and EnergyEfficiencyOptimizationofAutomotiveBatteryManagement Systems

Chen Shiyong (Guangzhou Polytechnic University，Guangzhou ，China)

【Abstract】 Currently，the power Battery Management System（BMS）is confronted with dual challengesof dynamicworkingconditionadaptabilityand fullifecycle management.Traditional methods haveastateestimationerror of more than 15% under extreme working conditions and an accuracy rate of early health state prediction of less than （20号 80% .This article integrates intellgent controland energy efficiencyoptimization technologies.Through deep learning, edgecomputinganddigital twin technologies，it promotes theupgradeofBMS from"passive protection"to "active optimization".Research shows that intelligent technologies can increase theeficiencyof low-temperature charging by more than 20% .Intelligent algorithms such as model predictive control，combined with digital twin models，can enhance the charging and discharging efficiency by 15% to 20% . Thistechnology can provide technical support for the research on thereliabilityand economy of new energy vehicle batteries.

【Keywords】automobile battery management system；inteligent control；energy eficiency optimization; battery performance

0 引言

当前动力电池管理系统（BatteryManagementSystem，BMS)正面临动态工况适应性与全生命周期管理的双重挑战。（剩余5115字）