Abstract
Based on the results of model and algorithm in Part1 for searching the optimal design parameters of vehicle suspensions using genetic algorithm, in Part 2, the simulation results with MATLAB Simulink combined with an optimal program are written to search the optimal design parameters of vehicle air suspension systems in two optimal conditions. The optimal results indicate that the DLC values at all axles of vehicle respectively reduce by 9.09 %, 10.71 %, 11.11%, 10.81 %, 8.82 % (in Case 1) and 14.29 %, 19.23 %, 20.00 %, 17.14 %, 12.12 % (in Case 2) in comparison with the original air suspension systems when vehicle moves on the ISO class C road surface at v= 20 m/s and full load. All these things indicate that using the genetic algorithm optimization method does not only reduce the tire dynamic loads acting on road surface but also improves the ride comfort. Finally, the optimum performance of vehicle suspension systems is considered and reassessed under different operating conditions. The evaluation results indicate that the optimum performance of the air suspension systems has better potential to improve the road friendliness which provides a ride comfort for road surfaces and vehicle.
Highlights
IntroductionIn order to improve the performance of the air suspension system for reducing the negative impact on the road surface, the control and optimization methods for air suspension systems are discussed in some of the following studies such as the control methods: the genetic LQG and PID control were used to control an air suspension system [1], the performance of the air suspension system of heavy trucks was analyzed with semi-active fuzzy control [2] and the two-bag air suspension system for heavy-duty vehicles was analyzed using the multi-body vehicle model [3], the optimization technique available in OptiY with SIMULINK simulation was used to search the optimal parameters of air spring of suspension system using vehicle dynamic model with 2 d.o.f [4], The air suspension system with independent height and stiffness tuning was analyzed and the geometric parameters of air spring were optimized [5], the glowworm swarm optimization proportional-integral-derivative controlling algorithm was designed to optimize magnetorheological damper for air suspensions [6], the vehicle suspension parameters of non-linear air spring was analyzed and optimized by using the multi-objective optimization method [7], and the optimization of suspension geometric parameters was analyzed and optimized using a double-loop multi-objective particle swarm optimization algorithm (DL-MOPSO) when the vehicle operates under various driving conditions [8]
In part 2 of this study, the simulation results by using MATLAB Simulink combined with an optimal program is written to solve the optimization problem of nonlinear air suspension parameters in two optimal conditions
The obtained the optimization results show that the DLC values of the optimal design parameters of air suspension systems at all axles of vehicle reduce in comparison with the initial air suspension systems of vehicle when vehicle moves on the ISO class
Summary
In order to improve the performance of the air suspension system for reducing the negative impact on the road surface, the control and optimization methods for air suspension systems are discussed in some of the following studies such as the control methods: the genetic LQG and PID control were used to control an air suspension system [1], the performance of the air suspension system of heavy trucks was analyzed with semi-active fuzzy control [2] and the two-bag air suspension system for heavy-duty vehicles was analyzed using the multi-body vehicle model [3], the optimization technique available in OptiY with SIMULINK simulation was used to search the optimal parameters of air spring of suspension system using vehicle dynamic model with 2 d.o.f [4], The air suspension system with independent height and stiffness tuning was analyzed and the geometric parameters of air spring were optimized [5], the glowworm swarm optimization proportional-integral-derivative controlling algorithm was designed to optimize magnetorheological damper for air suspensions [6], the vehicle suspension parameters of non-linear air spring was analyzed and optimized by using the multi-objective optimization method [7], and the optimization of suspension geometric parameters was analyzed and optimized using a double-loop multi-objective particle swarm optimization algorithm (DL-MOPSO) when the vehicle operates under various driving conditions [8]. The optimal parameters of the suspension systems as well as drum’s isolation system were found out using genetic algorithm (GA) [9, 10]. OPTIMAL DESIGN PARAMETERS OF AIR SUSPENSION SYSTEMS FOR SEMI-TRAILER TRUCK.
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