• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Industrial Informatics, IEEE Transactions on >Charging Pattern Optimization for Lithium-Ion Batteries With an Electrothermal-Aging Model
【24h】

Charging Pattern Optimization for Lithium-Ion Batteries With an Electrothermal-Aging Model

机译：电热老化模型优化锂离子电池充电方式

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

This paper applies advanced battery modeling and multiobjective constrained nonlinear optimization techniques to derive suitable charging patterns for lithium-ion batteries. Three important yet competing charging objectives, including battery health, charging time, and energy conversion efficiency, are taken into account simultaneously. These optimization objectives are first subject to a high-fidelity battery model that is synthesized from recently developed individual electrical, thermal, and aging models. The coupling relationship and multiple timescales among different model dynamics are identified. Furthermore, constraints are imposed explicitly on the current, voltage, state-of-charge, and temperature. Such a complex charging problem is solved by using an ensemble multiobjective biogeography-based optimization approach. As a result, two charging patterns, namely the constant current–constant voltage (CC–CV) and multistage CC–CV, are optimized to balance various combinations of charging objectives. Different tradeoffs and sensitive elements are compared and analyzed based on the Pareto frontiers. Illustrative results demonstrate that the proposed strategy can effectively offer feasible health-conscious charging with desirable tradeoffs among charging speed and energy conversion efficiency under different demand priorities.
机译：本文应用先进的电池建模和多目标约束非线性优化技术，得出适合锂离子电池的充电模式。同时考虑了三个重要但相互竞争的充电目标，包括电池健康，充电时间和能量转换效率。这些优化目标首先要遵循高保真电池模型，该模型是根据最近开发的单独的电，热和老化模型合成的。确定了不同模型动力学之间的耦合关系和多个时间尺度。此外，明确限制电流，电压，充电状态和温度。通过使用基于集合多目标生物地理的优化方法解决了这种复杂的收费问题。结果，优化了两种充电模式，即恒流-恒压（CC-CV）和多级CC-CV，以平衡充电目标的各种组合。根据帕累托边界对不同的权衡和敏感元素进行比较和分析。说明性结果表明，所提出的策略可以有效地提供可行的健康意识充电，并在不同需求优先级下在充电速度和能量转换效率之间取得理想的折衷。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号