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CPS: Synergy: Adaptive Management of Large Energy Storage Systems for Vehicle Electrification

CPS：协同：车辆电气化大型储能系统的自适应管理

基本信息

批准号：
1446117
负责人：
Kang Shin
金额：
$ 99.42万
依托单位：
Regents of the University of Michigan - Ann Arbor
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2015
资助国家：
美国
起止时间：
2015-01-01 至 2020-08-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1446117&HistoricalAwards=false
关键词：
CPS Synergy Adaptive Management Large

项目摘要

Large battery systems with 100s/1000s cells are being used to power various physical platforms. For example, automobiles are transitioning from conventional powertrains to (plug-in) hybrid and electric vehicles (EVs). To achieve the desired efficiency of EVs, significant improvements are needed in the architecture and algorithms of battery management. This project will develop a new comprehensive battery management architecture, called Smart Battery Management System (SBMS). The research is expected to bridge the wide gap existing between cyber-physical system (CPS) research and electrification industry communities, provide environment-friendly solutions, increase the awareness of CPS, and develop skilled human resources. This project will incorporate and enhance a battery management system (BMS) by including battery state-of-charge (SoC) and state-of-health (SoH) algorithms as well as power management strategies on both pack and cell levels. Specifically, it consists of five main research tasks: (i) design a dynamically reconfigurable energy storage system to tolerate harsh internal and external stresses; (ii) develop cell-level thermal management algorithms; (iii) develop efficient, dependable charge and discharge scheduling algorithms in hybrid energy storage systems; (iv) develop a comprehensive, diagnostic/prognostic (P/D) algorithm with system parameters adjusted for making optimal decisions; and (v) build a testbed and evaluate the proposed architecture and algorithms on the testbed. This research will advance the state-of-the-art in the management of large-scale energy storage systems, extending their life and operation-time significantly, which is key to a wide range of battery-powered physical platforms. That is, SBMS will enable batteries to withstand excessive stresses and power physical platforms for a much longer time, all at low costs. SBMS will also serve as a basic framework for various aspects of CPS research, integrating (cyber) dynamic control and P/D mechanisms, and (physical) energy storage system dynamics.

具有 100 节/1000 节电池的大型电池系统正被用来为各种物理平台供电。例如，汽车正在从传统动力系统过渡到（插电式）混合动力汽车和电动汽车（EV）。为了实现电动汽车所需的效率，需要对电池管理的架构和算法进行重大改进。该项目将开发一种新的综合电池管理架构，称为智能电池管理系统（SBMS）。该研究有望弥合信息物理系统（CPS）研究与电气化行业界之间存在的巨大差距，提供环境友好型解决方案，提高对信息物理系统（CPS）的认识，并培养熟练的人力资源。该项目将通过包括电池充电状态（SoC）和健康状态（SoH）算法以及电池组和电池级别的电源管理策略来整合和增强电池管理系统（BMS）。具体来说，它包括五个主要研究任务：（i）设计一个动态可重构的储能系统，以承受严酷的内部和外部压力； (ii) 开发电池级热管理算法； (iii) 开发混合储能系统中高效、可靠的充电和放电调度算法； (iv) 开发综合的诊断/预测 (P/D) 算法，调整系统参数以做出最佳决策； (v) 构建一个测试平台并在测试平台上评估所提出的架构和算法。这项研究将推进大规模储能系统管理的最先进水平，显着延长其寿命和运行时间，这是各种电池供电物理平台的关键。也就是说，SBMS 将使电池能够承受过大的压力，并以较低的成本为物理平台提供更长的时间。 SBMS 还将作为 CPS 研究各个方面的基本框架，集成（网络）动态控制和 P/D 机制以及（物理）储能系统动力学。