两种不同电池充电方式的比较

Goran Kujundžić, D. Bago, A. Bernadic
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引用次数: 0

摘要

摘要本文用模型预测控制(MPC)算法描述了电池堆的充电过程。算法采用温度模型和混合电模型。电池组由四个串联的阀控铅酸(VRLA)电池组成。优化的目标是在不违反约束的情况下对所提出的电池组进行充电,以保持电池的健康状态。通过闭环MPC仿真与实际MPC充电特性的对比,验证了MPC算法在电池充电中的应用。在此之前,传统的恒流恒压(CCCV)算法被证明是好的,考虑了退化效应,但没有考虑充电速度。将MPC算法与CCCV算法对所提出的电池堆进行充电比较,结果表明MPC算法优于CCCV算法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Comparison of Two Different Battery Charging Methods
Abstract This paper describes charging of battery stack using model predictive control (MPC) algorithm. Temperature model and hybrid electrical model are used in algorithm. The battery stack consists of four serially connected valve-regulated lead-acid (VRLA) batteries. The objective of the optimization is to charge the proposed battery stack without violating the constraints in order to maintain the battery health. Validation of MPC algorithm for battery charging is performed using comparison between closed-loop MPC simulations and obtained characteristics of actual MPC charging. Previously, the conventional constant current constant voltage (CCCV) algorithm was proved as good, taking into account the degradation effects but not considering the speed of the charging. The comparison between charging of proposed battery stack using MPC algorithm and CCCV algorithm is performed and the comparison in charging proves MPC algorithm as better compared to the CCCV algorithm.
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