Appraisal of meta-heuristics for a multi agent optimization of energy efficiency of driving wheels to attain sustainable energy

Mohammad Aligholizadeh


This paper examines various heuristic and meta-heuristic optimization approaches to maximize the tractive power efficiency as a substantial energy efficiency index of off-road vehicles. The experimental data were obtained utilizing a single-wheel tester and a soil bin facility under the effect of wheel load, slippage and velocity at three different levels. Global and local exploration of the search space was performed to achieve fast convergence to the optimal maxima. Imperialist competitive algorithm (ICA), particle swarm optimization (PSO), genetic algorithm (GA), and hybridized GA-PSO approaches were employed among computational optimization techniques for solving the energy efficiency problem. Assessment of the paradigms is described including the nonlinear problem function optimization. The obtained results revealed that ICA technique outperformed the other methods wherein the optimal energy efficiency of 69.01% was achieved at wheel load of 2.23 kN, velocity of 0.8 m/s and slippage of 14.33%. Adjustment of tire parameters at the proposed levels by the present study would potentially save a significant portion of energy associated with the adoption of off-road vehicles. 

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