In the automotive case study, we plan to develop a range optimization assistant for electric vehicles. Due to the weight and cost of the battery, the range of electric vehicles is limited, compared to conventional vehicles. In combination with the long time required for charging the battery, the limited capacity is one factor that limits their market acceptance. In order to maximise the range without compromising other qualities such as comfort or speed, a comprehensive assessment of the vehicle and its environment is necessary.
To achieve this goal, we model all relevant parts of the system and their impact on the battery’s state of charge.
The battery itself, the electric drive train, topography and roads, current traffic, the current weather, Cabin Thermal Control, as well as the driver itself with his/her requirements to thermal comfort and driving style. These models are created in native tools (such as Matlab) and then coupled, using the TWT CoSimulation Engine and the Functional Mockup Interface (FMI). In the further process of INTO-CPS, the tools of INTO-CPS will be used.
Benefits of simulating / using INTO-CPS
A modular CoSimulation approach is more flexible than a monolithic simulation, as it can be adapted more easily. Models can be exchanged to represent different physical components, or can be modelled with different level of detail.
Using the INTO-CPS tools, the design of the range optimisation assistant can be done virtually and many effects can be tested by simulation. Single components can be subsequently exchanged with more realistic models or data sources. This development process significantly simplifies and accelerates the design.