Abstract: To realize the real-time energy-saving mining of intelligent electric shovels, a multi-objective optimal mining trajectory planning method was put forward for intelligent electric shovels based on Non-dominated Sorting Genetic Algorithm-Ⅱ (NSGA-Ⅱ). Firstly, Lagrange's equations were used to establish the dynamic model of a working device for an intelligent electric shovel. Then, the mining trajectory was interpolated by adopting higher-order polynomials. Additionally, the issue of mining trajectory optimization was transformed into a polynomial coefficient optimization problem. Finally, minimizing the mining time and energy consumption per unit volume of material was taken as the optimization objective. By taking the motor performance and geometric conditions during the mining process as constraints, and utilizing the multi-objective optimization platform PlatEMO, NSGA-Ⅱ was adopted as the multi-objective optimization algorithm. The optimal solution set of multi-objective optimization Pareto was acquired by specifying the objective function and constraint function of the problem to be optimized. The weights were set in accordance with decision preference and the optimal solution was obtained by employing the TOPSIS method. Given this, the results of multi-objective optimal mining trajectory planning were acquired. From the results, the optimized mining trajectory was found to be able to satisfy the mining requirements of real-time energy saving.

Key words: intelligent electric shovel, dynamic model, Non-dominated Sorting Genetic Algorithm-Ⅱ (NSGA-Ⅱ), mining trajectory planning, multi-objective optimization