Battery and Heating Data in Real Driving Cycles

High-voltage batteries in battery electric vehicles face significant load fluctuations due to driving behavior. High accelerations cause high discharge currents, while regenerative braking leads to charging currents. This dynamic performance of the powertrain is contrasted by the almost constant load of the auxiliary consumers. The highest auxiliary consumption is generated by the heating and air conditioning system, which decreases the vehicles range significantly. This data set contains real driving data and simulated data. The real driving was recorded with a BMW i3 (60 Ah) and serves for the model development and validation of a full vehicle model consisting of the powertrain and the heating circuit. Each ride contains: Environmental data (temperature, elevation, etc.)Vehicle data (speed, throttle, etc.)Battery data (voltage, current, temperature, SoC)Heating circuit data (indoor temperature, heating power, etc.) Using the validated model, strategies for electrothermal recuperation, which describes the direct use of power in regenerative braking operations for heating, were implemented and the range advantage was determined. This approach was further developed to a peak power shaving. Depending on the drive power, the heating power is controlled. The simulation data* show this approach and the resulting improvement in range and battery life. *The corresponding paper was submitted.