A special design is needed for an unmanned tracked vehicle (UTV) to meet the requirements of off-road environments and complex tasks. A loose surface is the main terrain for tracked vehicles in off-road driving. Slope steering is inevitable while driving in such conditions; hence, its performance is a major concern for tracked vehicles on loose terrain. This study investigates the slope steering performance of a tracked vehicle. An improved dynamic steering model is proposed when considering the shear stress-shear displacement relation of soil at the track-ground interface. The influence of ground characteristics on the slope steering performance of a tracked vehicle is illustrated. The track slip rate is adopted as an index to evaluate the influence of typical vehicle structure parameters on the slope steering performance of a tracked vehicle. This study provides technical support for the design and optimization of UTV.

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The handling stability of tracked vehicles not only affects the handling convenience of drivers but is also an important part of vehicle active safety. A zero-differential steering controller for tracked vehicles with hydraulic-mechanical transmissions was designed in this paper. First, the working principle of the steer-by-wire systems of tracked vehicles was analyzed, and the vehicle speed calculation model was established. Then, the steering dynamics model of the tracked vehicle was established based on the shear stress model. Finally, based on the particle swarm optimization algorithm, the established tracked vehicle steering dynamics model was iteratively solved, and the optimal yaw rate gain 𝐾 𝑟 was calculated in real time and used for vehicle steering control. The steering control simulation model of tracked vehicles was established in MATLAB/Simulink, and the control effect of the designed steering controller was verified by the simulation. The control effect was evaluated by the comprehensive evaluation index of the handling stability. The simulation results showed that the steering controller based on the particle swarm optimization algorithm effectively improved the handling stability of the tracked vehicle and reduced the burden on the driver.INDEX TERMS particle swarm optimization algorithm, steer-by-wire system, tracked vehicle, zerodifferential steering controller

The high-speed steering control of tracked vehicles has been studied thoroughly, but the high-speed steering stability boundary of tracked vehicles has rarely been investigated. The establishment of a dynamics model with a high computational accuracy is the premise of studying the high-speed steering stability boundary of tracked vehicles. In this work, the track forces of tracked vehicles during steering were determined based on a shear stress model, and the steering dynamics model of tracked vehicles was established. A zero-differential-steering tracked vehicle was used as the object of study. The calculation results of the steering kinematics model and dynamics model of tracked vehicles under different steering conditions were studied in detail on sandy road surface environment, as well as the change laws of the steering trajectory, steering radius, vehicle centroid velocity, and steering slip angle. The steering trajectories of tracked vehicles on five kinds of roads under the same steering conditions were determined by simulations. By setting the critical condition for unstable steering, the corresponding relationship between the maximum circumferential velocity difference of the sprocket Δ u max , the minimum steering radius R min , the maximum sideslip angle β max , and the theoretical centroid speed v t h was obtained when the vehicle turned on five kinds of roads, and it was used to determine the high-speed steering stability boundary of tracked vehicles. The simulation results can provide a reference for the design of tracked vehicle steering mechanisms and high-speed steering control.

Since the internal heat transfer is a complicated process, the heat pipe heat exchanger of the engine has not been fully understood yet, which is originated from its extreme complexity. In theoretical studies, the involvement of two-phase flow and phase change processes usually simplifies the processing very much, and the model built differs too much from the actual one, resulting in reduced simulation accuracy. In this study, the prediction model of heat transfer and heat resistance of the heat pipe intercooler is established based on artificial neural networks (ANNs). Then the performance of the heat pipe intercooler from heat transfer and heat resistance aspects is investigated. The average relative error between the heat transfer prediction model and the test value is 3.6%, and the average relative error between the resistance prediction model and the test value is 12.68%, which shows that the prediction model can predict the thermal performance of heat pipe intercooler more accurately. Finally, the proposed model is applied to optimize the structural parameters of the heat pipe intercooler, and the optimal parameters are obtained accordingly. These optimal design parameters can provide the basis for further investigation and development of the heat pipe intercooler in diverse applications.