• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文OA文献 >Real-time Optimal Battery Thermal Management System Controller for Electric and Plug-in Hybrid Electric Vehicles
【2h】

Real-time Optimal Battery Thermal Management System Controller for Electric and Plug-in Hybrid Electric Vehicles

机译：电动和插电式混合动力汽车的实时最佳电池热管理系统控制器

页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

The objective of this thesis is to propose a real-time model predictive control (MPC)scheme for the battery thermal management system (BTMS) of given plug-in hybrid electricand electric vehicles (PHEV/EVs). Although BTMS control in its basic form can be wellrepresented by a reference tracking problem, there exists only little research in the literaturetaking such an approach. Due to the importance of a prediction component in thermalsystems, here the BTMS controller has been designed based on MPC theory to addressthis gap in the literature. Application of the controller to the baseline vehicles is thenexamined by several simulations with di erent optimization algorithms.By comparing the results of the predictive controller with those of the standard rulebased(RB) controller over a variety of driving scenarios, it is observed that the predictivecontroller signi cantly reduces the power consumption and provides a better tracking behaviour.Integrating trip prediction into the control algorithm is particularly important incases such as aggressive driving cycles and highly variable road-grades, where the standardBTMS scheme does not perform as e ectively due to the load current pro le.Moreover, based on the simulation results, the designed controller is observed to have aturnaround time between 10 s to 1 ms, and is thus applicable to the real-time automotivesystems.Prosperity of the proposed BTMS control methodology paves the way for the use ofmodel-based (MB) thermal management techniques, not only in future
机译：本文的目的是为给定插电式混合动力电动汽车（PHEV / EV）的电池热管理系统（BTMS）提出一种实时模型预测控制（MPC）方案。尽管基本的BTMS控制可以由参考跟踪问题很好地表示，但是在文献中采用这种方法的研究很少。由于热系统中预测组件的重要性，因此在此基于MPC理论设计了BTMS控制器来解决文献中的这一空白。然后通过使用不同优化算法的若干模拟对控制器在基准车辆上的应用进行了研究。通过在各种驾驶场景下将预测控制器的结果与标准RuleBase（RB）控制器的结果进行比较，可以观察到预测控制器大大降低了功耗并提供了更好的跟踪性能。在行驶周期激进和道路坡度变化很大的情况下，将行程预测集成到控制算法中尤其重要，在这种情况下，标准的BTMS方案由于负载而无法有效发挥作用此外，基于仿真结果，观察到设计的控制器具有10 s至1 ms的周转时间，因此适用于实时汽车系统。所提出的BTMS控制方法的繁荣为不仅仅在未来使用基于模型的（MB）热管理技术

著录项

  • 作者

    Masoudi Yasaman;

  • 作者单位
  • 年度 2017
  • 总页数
  • 原文格式 PDF
  • 正文语种 en
  • 中图分类

相似文献

  • 外文文献
  • 中文文献
  • 专利

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