A comprehensive evaluation method of electric power prediction models using multiple accuracy indicators is proposed. To obtain the preferred models, this paper selects a number of accuracy indicators that can reflect the accuracy of single-point prediction and the correlation of predicted data, and carries out a comprehensive evaluation. First, according to Dempster-Shafer (D-S) evidence theory, a new accuracy indicator based on the relative error (RE) is proposed to solve the problem that RE is inconsistent with other indicators in the quantity of evaluation values and cannot be adopted at the same time. Next, a new dimensionless method is proposed, which combines the efficiency coefficient method with the extreme value method to unify the accuracy indicator into a dimensionless positive indicator, to avoid the conflict between pieces of evidence caused by the minimum value of zero. On this basis, the evidence fusion is used to obtain the comprehensive evaluation value of each model. Then, the principle and the process of consistency checking of the proposed method using the entropy method and the linear combination formula are described. Finally, the effectiveness and the superiority of the proposed method are validated by an illustrative instance.

This paper investigates the design of a hybrid electric powertrain that includes an electric variable transmission (EVT), implemented as a dual rotor electric machine, and two mechanical gears that connect the EVT to the rest of the powertrain. The goal is to optimize the size of the EVT and the two mechanical gears, while minimizing fuel consumption, subject to performance requirements on top vehicle speed and acceleration time. A practical optimization methodology is proposed that decouples the multi-objective problem into three different control subproblems: a slow dynamic subproblem for fuel economy, a fast dynamic subproblem for acceleration performance and a static optimization subproblem for the top speed performance. Efficient dynamic programming formulations are presented to solve the two dynamic subproblems. Two different scenarios are discussed and analyzed, where the first one presents the influence of the EVT size on the vehicle performance and the second one delivers near optimal configurations of the EVT powertrain for different gear ratios. A case study is also carried out to compare the sizing results between the proposed method and an existing benchmard method, showing that the two electric machines of EVT powertrain could be reduced by 45% and 11.87% respectively, while powertrain performance could still be maintained at the same level.