Integrated cabin heating and powertrain thermal energy management for a connected hybrid electric vehicle

Connected and automated vehicles present significant opportunities for energy saving and efficiency, especially for hybrid electric vehicles. Information such as estimated trip duration, path, time, and ambient conditions can be utilized to predict the future thermal and traction loads for a connected vehicle. One of the most energy intensive sub-systems of a hybrid electric or fully electric vehicle is cabin heating in cold climates. In this work, an innovative co-optimization platform is developed to optimize: (i) cabin heating using combined electrical resistance heating and engine heat assist, (ii) multi-mode powertrain operation during charge depletion, and (iii) exhaust aftertreatment system thermal management to minimize catalyst light-off fuel penalty. To this end, a model-based cabin heating and powertrain optimization platform is created and tested using extensive experimental data from a plug-in hybrid electric vehicle. Vehicle's trip duration is estimated using vehicle connectivity data that is then used to forecast cabin heating and powertrain power demands. The results show the proposed integrated cabin and powertrain thermal management can lead to 10 % to 26% vehicle energy saving by testing for the United States Urban Dynamometer Driving Schedule and one real world drive cycle with varying elevations. In addition, the effect of variability of ambient temperature (-15 to 2 degrees C) on energy savings is studied using Monte Carlo simulations.