Connected BMS: Virtual Fleet Data for Battery Life Management

互联 BMS：用于电池寿命管理的虚拟车队数据

• 批准号: 79072
• 金额: $ 14.33万
• 依托单位: RICARDO UK LIMITED
• 依托单位国家: 英国
• 项目类别: Collaborative R&D
• 财政年份: 2020
• 资助国家: 英国
• 起止时间: 2020 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=79072
• 关键词: Connected; BMS; Virtual; Fleet; Data

Digital services and offerings that can extract insights from the large datasets that are generated by connected vehicle fleets. The Ricardo vision is for advanced monitoring and prognostics services to reduce electric vehicle battery failures in the field and extended battery life.The key objective of this project is to develop a test platform for monitoring and prognostics of battery health. Such monitoring management is part of a connected Battery Management System (BMS). A secondary objective is to investigate novel hybrid physics-based/data-driven prognostics algorithms for battery health management. A tertiary objective is to derive BMS calibration updates from the physics based/data-drive prognostics algorithm, that can then be applied via Software-over-the-Air (SOTA).There will be four focus areas in this project. Firstly, we will develop tools to virtually represent vehicle fleets. These virtual fleets will provide data to be ingested by the Connected BMS test platform. Secondly, we will address information flow from a CBMS to the test platform (Data-over-the-Air) Thirdly, we will focus on battery monitoring and prognostics algorithm development. Lastly, we will address information flow from the test platform back to the CBMS (Software-over-the-Air).There are three main innovations in this project. We will propose novel data storage methods on a Connected BMS, exploring techniques for data compression without degrading fidelity. We will develop innovative algorithms, combining physics-based modelling and data driven techniques, to generate insight into the battery health through statistical inference. We will derive from these algorithms techniques to automatically update the BMS calibrations (in the form of de-ratings) that will be provided, over the air, to the CBMS.

数字服务和产品，可以从互联车队生成的大数据集中提取见解。Ricardo的愿景是提供高级监测和预测服务，以减少现场电动汽车电池故障并延长电池寿命。该项目的关键目标是开发一个用于监测和预测电池健康状况的测试平台。这种监控管理是互联电池管理系统(BMS)的一部分。第二个目标是研究用于电池健康管理的新的基于物理和数据驱动的混合预测算法。第三个目标是从基于物理/数据驱动的预测算法中获取BMS校准更新，然后可以通过空中软件(SOTA)应用。这个项目将有四个重点领域。首先，我们将开发虚拟表示车队的工具。这些虚拟车队将提供要由所连接的BMS测试平台接收的数据。其次，我们将讨论从CBMS到测试平台(空中数据)的信息流。第三，我们将专注于电池监测和预测算法的开发。最后，我们将解决从测试平台返回到CBMS(空中软件)的信息流。我们将在互联的BMS上提出新的数据存储方法，探索在不降低保真度的情况下进行数据压缩的技术。我们将开发创新的算法，结合基于物理的建模和数据驱动的技术，通过统计推断来洞察电池的健康状况。我们将从这些算法中推导出自动更新BMS校准(以降级的形式)的技术，这些校准将通过空中提供给CBMS。