Advanced Cell State of Function Models for HEV operation

适用于 HEV 运行的高级细胞功能状态模型

• 批准号: EP/D079527/1
• 负责人: David Stone
• 金额: $ 18.85万
• 依托单位: University of Sheffield
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2006
• 资助国家: 英国
• 起止时间: 2006 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=EP%2FD079527%2F1
• 关键词: Advanced; Cell; State; Function; Models

Increasingly, electric and hybrid electric vehicles are being seen as a way to both lower emissions and raise vehicle efficiency for evermore energy concious consumers. Furthermore, the increasing trend towards more electric vehilces, with safety critical applications becoming dependant on electric actuation (brakes, steering etc), is highlighting the need for reliable and accurate prediction of state-of-charge, and state-of-health of the onboard battery pack, to ensure the pack will not fail under emergency conditions. The proposed work therefore underpins all advances within the more electric vehicle.The principle aim of this research is therefore to establish both computationally and memory efficient, accurate cell state-of-charge (SoC) and state-of-health (SoH) models, to underpin the estimation of cell state-of-function (SoF) for the next generation of vehicle batteries, with hybrid electric vehicle (HEV) requirements and valve regulated lead acid (VRLA) cells being used as a technology focus. Furthermore, the findings will be embodied in a technology demonstrator, a stand-alone hardware cell SoC / SoH / SoF monitor, which will be representative in terms of mass market technology.

对于越来越注重能源的消费者来说，电动汽车和混合动力汽车越来越被视为降低排放和提高车辆效率的一种方式。此外，随着安全关键应用变得依赖于电动驱动(刹车、转向等)，越来越多的电动汽车的趋势突显了对车载电池组充电状态和健康状态的可靠和准确预测的必要性，以确保电池组在紧急情况下不会失效。因此，这项研究的主要目的是建立计算和存储效率高、准确的电池荷电状态(SOC)和健康状态(SOH)模型，以支持下一代汽车电池的电池功能状态(SOF)的估计，混合动力汽车(HEV)的要求和阀控铅酸(VRLA)电池将作为技术重点。此外，这些发现将体现在一个技术演示中，即一个独立的硬件单元SoC/SOH/SOF监视器，它将在大众市场技术方面具有代表性。

项目成果

Novel battery model of an all-electric personal rapid transit vehicle to determine state-of-health through subspace parameter estimation and Kalman fi

全电动个人快速交通车辆的新型电池模型，通过子空间参数估计和卡尔曼 fi 确定健康状态

• 发表时间: 2008
• 作者: D Stone

Estimation of Transportation Battery Second Life for Use in Electricity Grid Systems

电网系统中使用的运输电池第二寿命的估计

• DOI: 10.1109/tste.2014.2303572
• 发表时间: 2014
• 期刊: IEEE Transactions on Sustainable Energy
• 影响因子: 8.8
• 作者: Strickland D