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Abstract Numerous researchers are committed to finding solutions to the path planning problem of intelligence-based vehicles. How to select the appropriate algorithm for path planning has always been the topic of scholars. To analyze the advantages of existing path planning algorithms, the intelligence-based vehicle path planning algorithms are classified into conventional path planning methods, intelligent path planning methods, and reinforcement learning (RL) path planning methods. The currently popular RL path planning techniques are classified into two categories: model based and model free, which are more suitable for complex unknown environments. Model-based learning contains a policy iterative method and value iterative method. Model-free learning contains a time-difference algorithm, Q-learning algorithm, state-action-reward-state-action (SARSA) algorithm, and Monte Carlo (MC) algorithm.

Abstract Recently, electric heavy-duty tractor-trailers (EHDTTs) have assumed significance as they present an immediate solution to decarbonize the transportation sector. Hence, to illustrate the economic viability of electrifying the freight industry, a detailed numerical model to estimate the battery capacity for an EHDTT is proposed for a route between Washington, DC, to Knoxville, TN. This model incorporates the effects of the terrain, climate, vehicular forces, auxiliary loads, and payload in order to select the appropriate motor and optimize the battery capacity. Additionally, current and near-future battery chemistries are simulated in the model. Along with equations describing vehicular forces based on Newton’s second law of motion, the model utilizes the Hausmann and Depcik correlation to estimate the losses caused by the capacity offset of the batteries. Here, a Newton-Raphson iterative scheme determines the minimum battery capacity for the required state of charge.

Abstract Due to their high strength and good flexibility, wire ropes are widely used in various intense applications. A wire rope will present complex wave mechanics, especially under impact conditions. In this article, wire ropes (steel core rope and hemp core rope alternately twisted) were used to study the wave dynamic response of steel wire ropes with preload shock. The transmission law of wire rope shock waves was obtained through actual measurements. The results showed that the compression wave and shear wave were generated and propagated along the rope after impact. The conduction of shear waves had significant reflection characteristics, and the reflected waves overlapped with each other. The conduction velocity of the impact shear wave of the steel core wire rope increased with increasing pretension. The peak tension caused by impact decayed exponentially.

Abstract Rubber elements present highly nonlinear mechanical properties affected by frequency and amplitude of excitation, prestrain and temperature, etc. Finite element (FE) models and lumped parameter models can be distinguished in the development of constitutive models of rubbers. Based on the concept of overlay model, different kinds of viscoelastic, or frequency-dependent models, and elastoplastic/friction, or amplitude-dependent models, are compared in terms of their modelling approach, parameters identification process and applications. Prestrain-dependent models and temperature-dependent thermo-mechanical models are also reviewed, including some special models which are not based on the concept of the overlay model. Experimental and computational studies of cylindrical bushings subjected to coupled deformation modes are analyzed and discussed.

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