Battery autonomy and drive range of Electric Vehicles could be improved by smart control of the power flows requested by equipped systems. In this paper, the authors propose two energy-saving strategies, acting respectively in the electric driveline consumption minimization and in the auxiliary power allocation policy. Developed solutions aim at the reduction of the power demand, both concerning e-powertrain and sub-components, not directly related to traction purpose, enhancing corresponding driveability distance. Evaluation of the result is done through a model-based approach, using a concept e-car proposed by Valeo and implemented in a co-simulation environment, between Amesim and Simulink. The investigated methodology appears as a useful tool for the optimal design of the vehicle sub-system and component.
48V electric vehicle powertrain optimal model-based design methodology / Yamamoto K.; Ponchant M.; Sellier F.; Favilli T.; Pugi L.; Berzi L.. - ELETTRONICO. - (2020), pp. 1-6. (Intervento presentato al convegno 2020 AEIT International Conference of Electrical and Electronic Technologies for Automotive, AEIT AUTOMOTIVE 2020 tenutosi a ita nel 2020).
48V electric vehicle powertrain optimal model-based design methodology
Favilli T.;Pugi L.;Berzi L.
2020
Abstract
Battery autonomy and drive range of Electric Vehicles could be improved by smart control of the power flows requested by equipped systems. In this paper, the authors propose two energy-saving strategies, acting respectively in the electric driveline consumption minimization and in the auxiliary power allocation policy. Developed solutions aim at the reduction of the power demand, both concerning e-powertrain and sub-components, not directly related to traction purpose, enhancing corresponding driveability distance. Evaluation of the result is done through a model-based approach, using a concept e-car proposed by Valeo and implemented in a co-simulation environment, between Amesim and Simulink. The investigated methodology appears as a useful tool for the optimal design of the vehicle sub-system and component.
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