EV HVAC Control Optimization: Energy Use Cut by 10%

  • Automobile
  • Optimization


Optimizing various parameters within a vehicle's Heating, Ventilation, and Air Conditioning (HVAC) system holds the potential to enhance power consumption efficiency and extend the driving range. In the past, control models were developed using simulators; however, these simulators inadequately represented the actual vehicle environment and operated at a slow pace. Consequently, the inability to replicate control performance in real vehicles resulted in delays in model development.


To overcome this challenge, a dynamics model was formulated to simulate the internal conditions of a vehicle, leveraging data collected from the air conditioning system of a real electric vehicle. Diverging from the conventional vehicle simulator, the trained model accurately predicted environmental changes within the vehicle, facilitating the creation of an efficient air conditioning system control model based on these predictions.

Value Delivered

This innovative approach led to the more efficient attainment of the target temperature compared to traditional control methods, achieving a notable 10% reduction in total energy consumption and a 5% increase in the total range. Extrapolating the impact, the implementation of this algorithm across all electric vehicles globally has the potential to extend the collective range by approximately 400 million kilometers.

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