Advanced Cell State of Function Models for HEV operation

越来越多的电动汽车和混合动力汽车被视为降低排放和提高汽车效率的一种方式，以满足越来越多的能源意识消费者。此外，电动汽车的发展趋势越来越明显，安全关键应用越来越依赖于电动驱动（刹车、转向等），这凸显了对车载电池组的充电状态和健康状况进行可靠和准确预测的需求，以确保电池组在紧急情况下不会失效。因此，这项提议的工作为电动汽车的所有进步奠定了基础。因此，本研究的主要目的是建立计算和存储效率高、准确的电池充电状态（SoC）和健康状态（SoH）模型，以混合动力汽车（HEV）要求和阀控铅酸（VRLA）电池为技术重点，为下一代汽车电池的电池功能状态（SoF）估计奠定基础。此外，研究结果将体现在技术演示中，即独立硬件单元SoC / SoH / SoF监视器，这将在大众市场技术方面具有代表性。

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.