Prediction of power losses in electric vehicle transmissions

传输功率损耗是电动汽车整体能量损耗的主要来源。相对而言，这一贡献比同等的ic动力车辆要大得多。因此，预测和最小化传输损耗的能力为提高效率从而扩大电动汽车的范围提供了重要途径。本项目将开发一个包含润滑油性能影响的电动汽车变速箱效率预测新模型。该方法利用热耦合齿轮润滑模型来准确预测齿轮齿摩擦以及轴承和搅拌损失。至关重要的是，该模型将使用实验获得的润滑油流变参数作为输入，这应该允许它区分不同的润滑油配方在整体齿轮箱效率方面。该模型旨在作为优化变速箱油和变速箱结构选择的工具，以提高电动汽车的效率和续航里程。结果将评估变速器损耗的趋势，选择现有的和新的油，并在一系列典型的电动汽车变速器的运行条件下。

Transmission power losses provide a major contribution to the overall energy loss in an electric vehicle. In relative terms, this contribution is much larger than in an equivalent IC-powered vehicle. Consequently, the ability to predict and minimise transmission losses provides an important avenue for improving the efficiency and thus extending the range of EVs. This project will develop a new model for prediction of EV gearbox efficiency including the influence of lubricant properties. The approach utilises a thermally-coupled gear lubrication model to accurately predict gear teeth friction as well as bearing and churning losses. Crucially, the model will use experimentally obtained lubricant rheology parameters as input which should allow it to differentiate between different lubricant formulations in terms of overall gearbox efficiency. The model is intended to be used as a tool for optimising the selection of transmission oils and gearbox architecture for improved efficiency and range of EVs. Results will assess the trends in transmission losses with a selection of existing and new oils and over a range of operating conditions typical of EV transmissions.