Integrated design of active suspension parameters for solving negative vibration effects of switched reluctance-in-wheel motor electrical vehicles based on multi-objective particle swarm optimization

2018 ◽  
Vol 25 (3) ◽  
pp. 639-654 ◽  
Author(s):  
Zhe Li ◽  
Ling Zheng
Keyword(s):  
Particle Swarm Optimization ◽  
Particle Swarm ◽  
Active Suspension ◽  
Optimization Method ◽  
Suspension System ◽  
Electromagnetic Excitation ◽  
Pareto Solution ◽  
Swarm Optimization ◽  
Multi Objective ◽  
Electrical Vehicles

As for the elastic layout of the direct-driven electric wheel system, the electromechanical coupling between the electromagnetic excitation of in-wheel driving motor and the weak damping system gives rise to negative vibration issues, which further deteriorate the dynamic performance of the electric vehicle. This paper presents a multi-objective optimization method for active suspension system to solve these issues by developing an integrated in-wheel motor electrical vehicles model. The unbalanced electromagnetic excitation from in-wheel driving motor is investigated by means of analytical and finite element methods. The Pareto solution set of optimal parameters are generated by the multi-objective particle swarm optimization method, and a comparison in vehicle dynamic performances is made to verify the targeted optimization method. The simulation results indicate that the optimized active suspension system attenuates the sensitivity of the vehicle system to electromagnetic excitation with a satisfactory balancing between vehicle ride comfort and stability as well as active suspension utilization.

scholarly journals Performance Analysis of a Semiactive Suspension System with Particle Swarm Optimization and Fuzzy Logic Control

2014 ◽  
Vol 2014 ◽  
pp. 1-12 ◽  
Author(s):  
Abroon Jamal Qazi ◽  
Clarence W. de Silva ◽  
Afzal Khan ◽  
Muhammad Tahir Khan
Keyword(s):  
Fuzzy Logic ◽  
Particle Swarm Optimization ◽  
Fuzzy Logic Controller ◽  
Ride Comfort ◽  
Particle Swarm ◽  
Active Suspension ◽  
Suspension System ◽  
Swarm Optimization ◽  
Quarter Model ◽  
Semiactive Suspension

This paper uses a quarter model of an automobile having passive and semiactive suspension systems to develop a scheme for an optimal suspension controller. Semi-active suspension is preferred over passive and active suspensions with regard to optimum performance within the constraints of weight and operational cost. A fuzzy logic controller is incorporated into the semi-active suspension system. It is able to handle nonlinearities through the use of heuristic rules. Particle swarm optimization (PSO) is applied to determine the optimal gain parameters for the fuzzy logic controller, while maintaining within the normalized ranges of the controller inputs and output. The performance of resulting optimized system is compared with different systems that use various control algorithms, including a conventional passive system, choice options of feedback signals, and damping coefficient limits. Also, the optimized semi-active suspension system is evaluated for its performance in relation to variation in payload. Furthermore, the systems are compared with respect to the attributes of road handling and ride comfort. In all the simulation studies it is found that the optimized fuzzy logic controller surpasses the other types of control.

Application of Particle Swarm Optimization in Cylinder Helical HGearH Multi-Objective Design

2011 ◽  
Vol 474-476 ◽  
pp. 2229-2233
Author(s):  
Yuan Bin Mo ◽  
Ji Zhong Liu ◽  
Bao Lei Wang ◽  
Wei Min Wan
Keyword(s):  
Particle Swarm Optimization ◽  
Optimization Design ◽  
Particle Swarm ◽  
Pso Algorithm ◽  
Optimization Method ◽  
Multi Objective Optimization ◽  
Swarm Optimization ◽  
Multi Objective

Cylinder helical gGear is widely used in industry. Multi-objective optimization design of the component is often met in its different application sSituation. In this paper a novel multi-objective optimization method based on Particle Swarm Optimization (PSO) algorithm is designed for applying to solve this kind of problem. A paradigm depicted in the paper shows the algorithm is practical.

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