A Review on Motor and Drive System for Electric Vehicle

Roy, Suchita; Pandey, Rahul

doi:10.1007/978-981-19-0979-5_23

Cited by 3 publications

(1 citation statement)

References 44 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The driving motor power selection is too large and will cause the motor to continue to run in a low-efficiency area, with huge energy consumption and reduced mileage. If the power is too small, the dynamic performance of the vehicle will be low, and the climbing performance and acceleration performance will be affected [29]. Too many power batteries will result in a large number of battery packs, increased vehicle weight and decreased power performance.…”

Section: Introductionmentioning

confidence: 99%

Study on Multi-Objective Optimization of Power System Parameters of Battery Electric Vehicles

Cao

Jiang

et al. 2023

Sustainability

View full text Add to dashboard Cite

The optimization of power parameters is the key to the design of pure electric vehicles. Reasonable matching of the relationship between various parameters can effectively reduce energy consumption and achieve energy sustainability. In this paper, several vehicle performance indexes such as maximum vehicle speed, acceleration time and power consumption per 100 km were used as optimization target vectors, and transmission ratio was used as optimization variable to establish the optimization problem of parameter matching. Then, the feasible domain of the transmission ratio was obtained by taking the lowest performance index of the vehicle as the constraint condition. In the feasible domain, the multi-objective genetic algorithm is used to solve the optimization problem. The Pareto optimal solution set is obtained for fixed ratio transmission and two-gear transmission, which is used as an alternative solution set. The final parameter-matching scheme is determined by comparing the alternative scheme set of different motors comprehensively. The results show that the competition relationship between multiple optimizable indexes can be described effectively by solving the Pareto front. Specifically, the Pareto optimal solution set for the motor A + fixed transmission scheme is 1.33~1.85; the Pareto optimal solution set for the motor A + 2 transmission scheme is [1.72, 0.98]~[2.99, 1.57], and the Pareto optimal solution set for the motor B + 2 transmission scheme is [2.99, 1.40]~[2.99, 1.57]. The motor A + fixed transmission scheme does not require A clutch and does not require designing a shift algorithm. Therefore, after comprehensive consideration, the motor A + fixed transmission ratio transmission scheme is set as the final scheme.

show abstract

Section: Introductionmentioning

confidence: 99%