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The drive torque for each motor can be performed independently for the distributed drive electric wheel loader (DDEWL). On the shovelling condition, the torque distribution can be optimised according to the tire load. Then the parasitic power and wheel slippage can be reduced, and the tractive force and efficiency are improved. In this study, the singular value decomposition unscented Kalman filter is adopted to estimate the shovelling load. Based on the estimated shovelling load, the vertical tire force is calculated. The tire load rate is used to build the optimisation objective. The drive antiskid is set as the boundary condition. And a modified particle swarm optimisation is applied as the optimisation algorithm. A wheel loader is utilised for the testing data acquisition. Based on the acquired testing data, the comparative study about the optimisation and un-control strategies is operated. The results show that the slippage occurs less in the optimisation strategy, and the tractive force and efficiency are higher than the un-control strategy. In this study, the feasibility of the shovel load estimator is verified. The advantages of the optimisation strategy of distributed drive electric wheel loaders in shovelling process are analysed.

Optimisation strategy of torque distribution for the distributed drive electric wheel loader based on the estimated shovelling load