Based on the WLTP driving cycle, we simulate different scenarios depending on the used driving mode (ECO, Sport, Comfort) and ambient conditions (outside temperature) and consider or discuss the average energy consumption and the achieved range. One focus of this model is the representation of a Li-Ion battery and the required cooling and heating system. For this purpose, we present a cross-domain system simulation model from ESI SimulationX® and present properties and handling as well as analysis of the model (see figure). ) or environmental conditions (temperature, elevation profile). ), driver behavior (HVAC, control, driving mode. For energy consumption calculation and range determination, we take into account diverse influencing factors, such as vehicle characteristics (air/rolling resistance, weight. In our presentation, we use the example of a battery electric vehicle (BEV) to demonstrate a specific system topology with dimensioned system components controlled by a predictive operation strategy. A powerful for system identfication is available at the business site How it works. Such methods close the gap between purely theoretical simulation results and the actual driving experience with the help of realistic simulations. In the industrial environment, it is often difficult to obtain process models due to noisy data. For manual system inputs, the control settings can be adjusted at run time using the dashboard controls. For predefined system inputs, the control settings for the HVAC system is specified in a signal builder block. In addition to general demands for more comprehensive and accurate results in a shorter time, the automotive industry requires virtual design and test methods to reuse powertrain models and associated data throughout the development process, including for driving performance as well as energy consumption estimation. The model can be simulated in two modes: predefined system inputs or manual system inputs. The goal in the entire system design or development of vehicles is to find the optimal balance between vehicle performance, driving comfort and operating costs.
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