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Wheel loader shovel loading operation tests showed that when the tire slips, it not only causes waste of the engine power, but also increases the tire wear. In this paper, the regression prediction model is combined with the electro-hydraulic proportional control technology. For the first time, the method of adjusting the posture of the working device is proposed to realize the skid-proof shovel control strategy of the wheel loader. In this control strategy: (1) The electro-hydraulic proportional control technology applied to this wheel loader is introduced. (2) The load spectrum of the wheel loader is analyzed during the shovel loading operation. Moreover, combined with the drive shaft torque, pilot pressure and boom cylinder displacement, the particle swarm optimization-support vector machine (PSO-SVM) algorithm is used to complete the construction of the regression prediction model of the boom cylinder displacement. (3) A controller is designed based on the fractional-order PID control algorithm. The skid-proof control strategy is simulated and verified by constructing the joint simulation model. The corresponding program is prepared in the hydraulic system controller and the effectiveness of the control strategy and algorithm are verified by the wheel loader shovel loading operation.

The pivotal steering ability of vehicles is important in the case of narrow steering space. In this study, a pivot steering system for the rescue vehicle is designed, and the 1D + 3D co-simulation model is established based on automatic dynamic analysis of mechanical systems (Adams) and advanced modelling environment for performing simulation of engineering systems (AMESim). The dynamic analysis of the pivot steering system has been compared with the theoretical calculations, which proved the correction of the model. In addition, through the simulation, the authors can hold the conclusion that the tyre cornering stiffness has a great influence on the pivot steering system.

In order to improve the dynamic quality of traditional sliding mode control for an active suspension system, an optimal sliding mode control (OSMC) based on a genetic algorithm (GA) is proposed. First, the overall structure and control principle of the active suspension system are introduced. Second, the mathematical model of the quarter car active suspension system is established. Third, a sliding mode control (SMC) controller is designed to manipulate the active force to control the active suspension system. Fourth, GA is applied to optimize the weight coefficients of an SMC switching function and the parameters of the control law. Finally, the simulation model is built based on MATLAB/Simulink (version 2014a), and the simulations are performed and analyzed with the proposed control strategy to identify its performance. The simulation results show that the OSMC controller tuned using a GA has better control performance than the traditional SMC controller.