Implementation of vehicle model in GT-Suite for energy efficiency studies

Abstract

Electric vehicles are comprised of heat-generating components. The operation of the battery, electric motors and their inverters, and the charging components produce heat output that needs to be managed. A battery electric vehicle’s thermal management system is responsible for accumulating all the heat from these components, located at different places along with the vehicle, and transferring it to the ambient. In cold conditions, the purpose of the system is reversed, as it needs to maintain and produce the heat required to bring the components up to operational temperature. Thus, the system needs to be adaptable to internal and external parameters and choose the most efficient strategy to fulfil its predetermined goals. To generate the response of the thermal models, a battery current, motor torque and speed input from a vehicle model are needed. The battery current determines the battery’s heat generation during charging or discharging, while the motor’s torque and speed the losses or efficiency during its operation. Since the component function and efficiency depends on their respective temperatures, there is a co-dependence or temperature loop between the input and the output of each component. Therefore, a model is created in GT-Suite with VSIM as a baseline and a source for the vehicle’s configuration data. Initially, the vehicle model in GT-Suite needs to achieve similar results to the VSIM output. Some deviation is expected due to the different modelling and simulation procedures between the two software. Within Volvo Cars, GT-Suite contains all the thermal models for the electrical driveline components of the vehicle model. Therefore, the integration of the vehicle model to the CVTM satisfies the co-dependence mentioned above, and the complete vehicle simulation with a speed profile being the input can be completed under one software. This increases the accuracy of the simulation and the degrees of freedom regarding the parameter change, like the shutter position, which alters the aerodynamic coefficients during subsequent simulations. In addition to this, the data import and simulation setup and execution can be automated through Python, vastly shortening the workload. The result of this work is a complete vehicle model, able to reproduce with high accuracy the performance and thermal parameters during a driving cycle and can be used for verification and validation purposes and control development and tuning.