Cooling System Energy Consumption Reduction through a Novel All-Electric Powertrain Traction Module and Control Optimization

Simone Lombardi, Manfredi Villani, Daniele Chiappini and Laura Tribioli
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Simone Lombardi: Department of Industrial Engineering, University of Rome Niccolò Cusano, Via Don Carlo Gnocchi, 3, 00195 Rome, Italy
Manfredi Villani: Department of Industrial Engineering, University of Rome Niccolò Cusano, Via Don Carlo Gnocchi, 3, 00195 Rome, Italy
Daniele Chiappini: Department of Industrial Engineering, University of Rome Niccolò Cusano, Via Don Carlo Gnocchi, 3, 00195 Rome, Italy
Laura Tribioli: Department of Industrial Engineering, University of Rome Niccolò Cusano, Via Don Carlo Gnocchi, 3, 00195 Rome, Italy

Energies, 2020, vol. 14, issue 1, 1-22

Abstract: In this work, the problem of reducing the energy consumption of the cooling circuit for the propulsion system of an all-electric vehicle is approached with two different concepts: improvement of the powertrain efficiency and optimization of the control strategy. Improvement of the powertrain efficiency is obtained through a modular design, which consists of replacing the electric powertrain with several smaller traction modules whose powers sum up to the total power of the original powertrain. In this paper, it is shown how modularity, among other benefits, also allows reducing the energy consumption of the cooling system up to 54%. The energy consumption of the cooling system is associated with two components: the pump and the fan. They produce a so-called auxiliary load on the battery, reducing the maximum range of the vehicle. In conventional cooling systems, the pump and the fan are controlled with a thermostat, without taking into account the energy consumption. Conversely, in this work a control strategy to reduce the auxiliary loads is developed and compared with the conventional approach, showing that the energy consumption of the cooling system can be reduced up to 27%. To test the control strategy, numerical simulations have been carried out with a 1-D model of the cooling system. On the other hand, all the thermal loads of the components have been calculated with a vehicle simulator, which is able to predict the vehicle’s behavior under different driving cycles.

Keywords: electric vehicle; propulsion cooling system; modularity; thermal management; control optimization (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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