Techniques to Evaluate Energy Efficiency and Performance of an Electric Vehicle by Leveraging Co-Simulation 2021-26-0367

During the development phase of any Powertrain component/subsystem for a conventional ICE or an XEV (Hybrid/Battery Electric Vehicle), system Energy efficiency and Performance improvement simulations are a very important step to prove the worthiness of the product before we can advance to building Prototypes, Vehicle level Integration, Testing, analysis and benefit’s evaluation phases. This work describes how two simulation tools have been leveraged effectively for Energy efficiency and Performance simulations for an Electric vehicle. Schaeffler has an internal Physical Modelling Tool (PMT) for building vehicle level models. This tool has readymade physical blocks for various Mechanical and Electrical components. These blocks can be parameterized as per required specifications. The powertrain subsystems like the Battery, BLDC Motor, Vehicle Dynamics and the Multi-speed transmission consisting of various mechanical elements have been modelled and parametrized using this tool. This tool is the front end of the Co-simulation. The Physical model is used to provide various model inputs like Drive cycles, Motor and Battery characteristics, Throttle and Gear Shift maps. On the backend we leverage the Equation and Logics modelling capabilities of Matlab Simulink. The Driver and the Vehicle models have been made using Matlab Simulink. The Driver model consists of logics which provides various outputs like Throttle, Brake and vehicle Power demand. The Vehicle models consists of algorithms which provides outputs like Desired Motor Torque and transmission gear position. These two Matlab Simulink models are converted into Standalone Functions/Codes and integrated with the Physical model. Thus, all the three models are looped to each other. The advantage of this co-simulation is that the user must only interact with only one tool, at the same time reaping the benefit of the other tool/s in the background. This utilizes the best of both worlds. Co-simulation is a very good technique to simulate complex subsystems by leveraging advantages of multiple Simulation tools to get faster and accurate results.