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Multi-Disciplinary Optimisation of Road Vehicle Chassis Subsystems

Author

Listed:
  • Liunan Yang

    (Department of Mechanical Engineering, Politecnico di Milano, 20156 Milan, Italy
    Chongqing Changan Automobile Company, Chongqing 401120, China
    College of Mechanical and Vehicle Engineering, Chongqing University, Chongqing 400044, China)

  • Massimiliano Gobbi

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

  • Gianpiero Mastinu

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

  • Giorgio Previati

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

  • Federico Ballo

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

Abstract

Two vehicle chassis design tasks were solved by decomposition-based multi-disciplinary optimisation (MDO) methods, namely collaborative optimisation (CO) and analytical target cascading (ATC). A passive suspension system was optimised by applying both CO and ATC. Multiple parameters of the spring and damper were selected as design variables. The discomfort, road holding, and total mass of the spring–damper combination were the objective functions. An electric vehicle (EV) powertrain design problem was considered as the second test case. Energy consumption and gradeability were optimised by including the design of the electric motor and the battery pack layout. The standard single-level all-in-one (AiO) multi-objective optimisation method was compared with ATC and CO methods. AiO methods showed some limitations in terms of efficiency and accuracy. ATC proved to be the best choice for the design problems presented in this paper, since it provided solutions with good accuracy in a very efficient way. The proposed investigation on MDO methods can be useful for designers, to choose the proper optimisation approach, while solving complex vehicle design problems.

Suggested Citation

  • Liunan Yang & Massimiliano Gobbi & Gianpiero Mastinu & Giorgio Previati & Federico Ballo, 2022. "Multi-Disciplinary Optimisation of Road Vehicle Chassis Subsystems," Energies, MDPI, vol. 15(6), pages 1-21, March.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:6:p:2172-:d:772552
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