Fuzzy logic and proportional integral derivative based multi-objective optimization of active suspension system of a 4×4 in-wheel motor driven electrical vehicle

Bingül Ö., YILDIZ A.

JVC/Journal of Vibration and Control, 2022 (SCI-Expanded) identifier

  • Publication Type: Article / Article
  • Publication Date: 2022
  • Doi Number: 10.1177/10775463211062691
  • Journal Name: JVC/Journal of Vibration and Control
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, Aerospace Database, Aquatic Science & Fisheries Abstracts (ASFA), Communication Abstracts, Compendex, INSPEC, Metadex, zbMATH, Civil Engineering Abstracts
  • Keywords: Electric vehicle, genetic algorithm, in-wheel motor, multi-objective optimization, rollover effect
  • Bursa Uludag University Affiliated: Yes


© The Author(s) 2022.This paper considers fuzzy logic and proportional integral derivative based multi-objective optimization of a non-linear active suspension system of a 4 × 4 in-wheel motor-driven electric vehicle by using the non-dominated sorting genetic algorithm II. The active suspension system of the electric vehicle and its controllers are optimized to achieve International Organization for Standardization2631-1 ride comfort and health criteria, also providing the actual working conditions such as roll angle and tire load transfers simultaneously for driving safety. In this regard, a non-linear full electrical vehicle model with quadratic tire and cubic suspension stiffnesses with 11 degrees of freedom and a seat-driver model with 5 degrees of freedom are implemented and optimized regarding seven objective functions determined from the root mean square of head and seat accelerations, crest factor, vibration dose value, the ratio of head and seat accelerations, the ratio of the upper torso and seat acceleration, root mean square upper torso acceleration, and root mean square of suspension, tire, and in-wheel motor displacements. The design variables of the optimization problem are chosen as the stiffnesses and damping coefficients of the suspension, in-wheel motors, and seat, as well as the parameters of the proportional derivative and fuzzy logic controllers. The obtained results demonstrate that significant improvements can be achieved by using a controller over the passive systems. It is also noted that the fuzzy logic controller improves ride comfort and the health criterion over proportional derivative system up to 13%, while the load transfer ratio index showed no adverse change between models concerning the rollover condition. The outcomes of this work clearly state that significant improvements, in terms of vibration exposure, can be achieved with the help of reducing the vibration amplitude of an in-wheel motor-driven electrical vehicle active suspension system by using multi-objective optimization considering a non-linear full vehicle model and realistic working conditions such as tire load transfer and vehicle body roll during cornering circumstances. Thus, obtained results are of utmost importance for manufacturers about the active suspension design process providing both a safe and comfortable driving of in-wheel driven electric vehicles.