A key feature achievable by electric vehicles with multiple motors is torque-vectoring. Many control techniques have been developed to harness torque-vectoring in order to improve vehicle safety and energy efficiency. The majority of the existing contributions only deal with specific aspects of torque-vectoring. This paper presents an integrated approach allowing a smooth coordination among the main blocks that constitute a torque-vectoring control framework: (1) a reference generator, that defines target yaw rate and sideslip angle; (2) a high level controller, that works out the required total torque and yaw moment at the vehicle level; (3) a low level controller, that maps the required force and yaw moment into individual wheel torque demands. In this framework, the driver can select one among a number of driving modes that allow to change the vehicle cornering response and, as a second priority, maximise energy efficiency. For the first time, the selectable driving modes include an “Energy efficiency” mode that uses torque-vectoring to prioritise the maximisation of the vehicle energy efficiency, thus further increasing the vehicle driving range. Simulation results show the effectiveness of the proposed framework on an experimentally validated 14 degrees of freedom vehicle model.

具有多个电动机的电动车辆可实现的关键功能是转矩矢量化。为了提高车辆安全性和能源效率，已经开发出许多控制技术来利用转矩矢量化。现有的大多数贡献仅涉及转矩矢量的特定方面。本文提出了一种集成的方法，该方法可以在构成转矩矢量控制框架的主要模块之间进行平稳协调：（1）参考发电机，用于定义目标偏航角速度和侧滑角；（2）一个高水平控制器，可以在车辆水平上计算出所需的总扭矩和横摆力矩；（3）低水平控制器，它将所需的力和偏航力矩映射到各个车轮扭矩需求中。在这个框架中，驾驶员可以在多种驾驶模式中选择一种，以改变车辆的转弯响应，并作为第二优先级，最大程度地提高能源效率。可选的驾驶模式首次包括“能源效率”模式，该模式使用扭矩矢量化来优先考虑车辆能效的最大化，从而进一步增加了车辆的行驶里程。仿真结果表明了该框架在经过实验验证的14自由度车辆模型上的有效性。