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An Ultra-Efficient Lightweight Electric Vehicle—Power Demand Analysis to Enable Lightweight Construction

Author

Listed:
  • Pietro Stabile

    (Department of Mechanical Engineering, Politecnico di Milano, 20156 Milan, Italy)

  • Federico Ballo

    (Department of Mechanical Engineering, Politecnico di Milano, 20156 Milan, Italy)

  • Gianpiero Mastinu

    (Department of Mechanical Engineering, Politecnico di Milano, 20156 Milan, Italy)

  • Massimiliano Gobbi

    (Department of Mechanical Engineering, Politecnico di Milano, 20156 Milan, Italy)

Abstract

A detailed analysis of the power demand of an ultraefficient lightweight-battery electric vehicle is performed. The aim is to overcome the problem of lightweight electric vehicles that may have a relatively bad environmental impact if their power demand is not extremely reduced. In particular, electric vehicles have a higher environmental impact during the production phase, which should be balanced by a lower impact during the service life by means of a lightweight design. As an example of an ultraefficient electric vehicle, a prototype for the Shell Eco-marathon competition is considered. A “tank-to-wheel” multiphysics model (thermo-electro-mechanical) of the vehicle was developed in “Matlab-Simscape”. The model includes the battery, the DC motors, the motor controller and the vehicle drag forces. A preliminary model validation was performed by considering experimental data acquisitions completed during the 2019 Shell Eco-marathon European competition at the Brooklands Circuit (UK). Numerical simulations are employed to assess the sharing of the energy consumption among the main dissipation sources. From the analysis, we found that the main sources of mechanical dissipation (i.e., rolling resistance, gravitational/inertial force and aerodynamic drag) have the same role in the defining the power consumption of such kind of vehicles. Moreover, the effect of the main vehicle parameters (i.e., mass, aerodynamic coefficient and tire rolling resistance coefficient) on the energy consumption was analyzed through a sensitivity analysis. Results showed a linear correlation between the variation of the parameters and the power demand, with mass exhibiting the highest influence. The results of this study provide fundamental information to address critical decisions for designing new and more efficient lightweight vehicles, as they allow the designer to clearly identify which are the main parameters to keep under control during the design phase and which are the most promising areas of action.

Suggested Citation

  • Pietro Stabile & Federico Ballo & Gianpiero Mastinu & Massimiliano Gobbi, 2021. "An Ultra-Efficient Lightweight Electric Vehicle—Power Demand Analysis to Enable Lightweight Construction," Energies, MDPI, vol. 14(3), pages 1-18, February.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:3:p:766-:d:491215
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    References listed on IDEAS

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    1. Klaus Kivekäs & Antti Lajunen & Jari Vepsäläinen & Kari Tammi, 2018. "City Bus Powertrain Comparison: Driving Cycle Variation and Passenger Load Sensitivity Analysis," Energies, MDPI, vol. 11(7), pages 1-26, July.
    2. Mahmoudzadeh Andwari, Amin & Pesiridis, Apostolos & Rajoo, Srithar & Martinez-Botas, Ricardo & Esfahanian, Vahid, 2017. "A review of Battery Electric Vehicle technology and readiness levels," Renewable and Sustainable Energy Reviews, Elsevier, vol. 78(C), pages 414-430.
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    Cited by:

    1. Zoltán Pusztai & Péter Kőrös & Ferenc Szauter & Ferenc Friedler, 2023. "Implementation of Optimized Regenerative Braking in Energy Efficient Driving Strategies," Energies, MDPI, vol. 16(6), pages 1-20, March.
    2. Pietro Stabile & Federico Ballo & Giorgio Previati & Giampiero Mastinu & Massimiliano Gobbi, 2023. "Eco-Driving Strategy Implementation for Ultra-Efficient Lightweight Electric Vehicles in Realistic Driving Scenarios," Energies, MDPI, vol. 16(3), pages 1-19, January.
    3. Zoltán Pusztai & Péter Kőrös & Ferenc Szauter & Ferenc Friedler, 2022. "Vehicle Model-Based Driving Strategy Optimization for Lightweight Vehicle," Energies, MDPI, vol. 15(10), pages 1-20, May.

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