Using Machine Learning to Optimize Energy Consumption of HVAC Systems in Vehicles
The detachment and calculation of functionalities from a vehicle into a cloud creates new chances. By linking different data sources with the in-vehicle data in the cloud, an optimization of these functionalities in terms of energy efficiency can be applied. For example, the Heating, Ventilation and Air Conditioning (HVAC) consumes up to 30% of total energy in a vehicle. Electric vehicles in particular lead to these high values because they are not able to recover the waste heat from combustion engines for interior heating. Therefore, the optimization of energy efficient strategies with respect to the vehicle energy management system becomes more relevant. Forecasts of the interior vehicle temperature are directly related to the HVAC energy consumption. This work focuses on the implementation and accuracy evaluation of Recurrent Neural Networks (RNN) for interior vehicle temperature forecasting.
KeywordsHeating Ventilation and Air Conditioning (HVAC) Energy efficiency Internet of Things Machine learning
- 1.Traub, M., Vögel, H.J., Sax, E., Streichert, T., Härri, J.: Digitalization in automotive and industrial systems. In: Proceedings of 2018 Design Automation Test in Europe Conference and Exhibition DATE 2018, January 2018, pp. 1203–1204 (2018). https://doi.org/10.23919/DATE.2018.8342198
- 3.Kurdikeri, R.B., Raju, A.B.: Comparative study of short-term wind speed forecasting techniques using artificial neural networks. In: Proceedings of 2018 International Conference on Current Trends Towards Converging Technologies, ICCTCT 2018, pp. 1–5 (2018). https://doi.org/10.1109/ICCTCT.2018.8550849
- 5.Greff, K., Srivastava, R.K., Koutnik, J., Steunebrink, B.R., Schmidhuber, J.: LSTM: Search Space Odyssey. CoRR. abs/1503.0, pp. 2222–2232 (2015)Google Scholar