A Real-Time Approach for Thermal Comfort Management in Electric Vehicles
| Autor: | Emmanuel Boudard, Florence Ossart, Mohamed Bakhouya, Anas Lahlou, Francis Roy |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
0209 industrial biotechnology
battery electric vehicle thermal comfort HVAC energy management real-time control dynamic programming Control and Optimization Energy management Computer science 020209 energy medicine.medical_treatment Energy Engineering and Power Technology 02 engineering and technology lcsh:Technology Automotive engineering 020901 industrial engineering & automation Real-time Control System Thermal 0202 electrical engineering electronic engineering information engineering medicine Battery electric vehicle Electrical and Electronic Engineering Engineering (miscellaneous) Renewable Energy Sustainability and the Environment business.industry lcsh:T Thermal comfort Energy consumption Traction (orthopedics) Optimal control business Energy (miscellaneous) |
| Zdroj: | Energies, Vol 13, Iss 4006, p 4006 (2020) Energies; Volume 13; Issue 15; Pages: 4006 |
| ISSN: | 1996-1073 |
| Popis: | The HVAC system represents the main auxiliary load in electric vehicles, but passengers’ thermal comfort expectations are always increasing. Hence, a compromise is needed between energy consumption and thermal comfort. The present paper proposes a real-time thermal comfort management strategy that adapts the thermal comfort according to the energy available for operating the HVAC system. The thermal comfort is evaluated thanks to the “Predicted Mean Vote”, representative of passenger’s thermal sensations. Based on traffic and weather predictions for a given trip, the algorithm first estimates the energy required for the traction and the energy available for thermal comfort. Then, it determines the best thermal comfort that can be provided in these energetic conditions and controls the HVAC system accordingly. The algorithm is tested for a wide variety of meteorological and traffic scenarios. Results show that the energy estimators have a good accuracy. The absolute relative error is about 1.7% for the first one (traction), and almost 4.1% for the second one (thermal comfort). The effectiveness of the proposed thermal comfort management strategy is assessed by comparing it to an off-line optimal control approach based on dynamic programming. Simulation results show that the proposed approach is near-optimal, with a slight increase of discomfort by only 3%. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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