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Optimal Management of Thermal Comfort and Driving Range in Electric Vehicles
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The HVAC system represents the main auxiliary load in battery-powered electric vehicles (BEVs) and requires efficient control approaches that balance energy saving and thermal comfort. On the one hand, passengers always demand more comfort, but on the other hand the HVAC system consumption strongly impacts the vehicle’s driving range, which constitutes a major concern in BEVs. In this paper, a thermal comfort management approach that optimizes the thermal comfort while preserving the driving range during a trip is proposed. The electric vehicle is first modeled together with the HVAC and the passengers’ thermo-physiological behavior. Then, the thermal comfort management issue is formulated as an optimization problem solved by dynamic programing. Two representative test-cases of hot climates and traffic situations are simulated. In the first one, the energetic cost and ratio of improved comfort is quantified for different meteorological and traffic conditions. The second one highlights the traffic situation in which a trade-off between the driving speed and thermal comfort is important. A large number of weather and traffic situations are simulated and results show the efficiency of the proposed approach in minimizing energy consumption while maintaining a good comfort.
Title: Optimal Management of Thermal Comfort and Driving Range in Electric Vehicles
Description:
The HVAC system represents the main auxiliary load in battery-powered electric vehicles (BEVs) and requires efficient control approaches that balance energy saving and thermal comfort.
On the one hand, passengers always demand more comfort, but on the other hand the HVAC system consumption strongly impacts the vehicle’s driving range, which constitutes a major concern in BEVs.
In this paper, a thermal comfort management approach that optimizes the thermal comfort while preserving the driving range during a trip is proposed.
The electric vehicle is first modeled together with the HVAC and the passengers’ thermo-physiological behavior.
Then, the thermal comfort management issue is formulated as an optimization problem solved by dynamic programing.
Two representative test-cases of hot climates and traffic situations are simulated.
In the first one, the energetic cost and ratio of improved comfort is quantified for different meteorological and traffic conditions.
The second one highlights the traffic situation in which a trade-off between the driving speed and thermal comfort is important.
A large number of weather and traffic situations are simulated and results show the efficiency of the proposed approach in minimizing energy consumption while maintaining a good comfort.
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