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Technical Paper

Tooth Profile Modification Analysis of Fine-Pitch Planetary Gears for High-Speed Electric Drive Axles Based on KISSsoft

2021-12-31
2021-01-7016
According to the requirements of high transmission ratio and high load torque of high-speed electric drive axle planetary gear system, the design and analysis of fine-pitch planetary gear system with small modulus, small pressure angle and high full tooth height of are carried out. In order to improve the bearing capacity of gear and reduce gear meshing noise, the tooth profile modification parameters of gear system are optimized. In this paper, the tooth modification methods are analyzed and the gear train parameters are determined. The influence degree of different tooth modification methods on the transmission performance of the gear train is determined by orthogonal experiment method. The transmission error is reduced, the stress fluctuation is improved, and the gear meshing performance is greatly improved by adopting the appropriate modification scheme, which proves the effectiveness of the tooth modification scheme.
Technical Paper

Simultaneous Optimization of Power Train Parameter and Control Strategy in a Plug-In Hybrid Electric Bus

2015-09-29
2015-01-2828
In the Plug-in hybrid electric bus, the power train parameter and control strategy significantly affect the economy and dynamic performance. Thus, the simultaneous optimization of power train parameter and control strategy is designed for the trade-off between the dynamic and economic performance. Depending on the parallel electric auxiliary control strategy in a plug-in hybrid electric bus, a vehicle dynamic simulation model is built with the software AVL Cruise. Aiming at the minimization of equivalent gas consumption and acceleration time from 0 to 50kmph, the gear ratio, final drive ratio, gear shifting strategy and control strategy are chosen as optimal variable, which significantly impact power performance and fuel economy. The driving performance and the driving range with full battery are considered as constraints. Based on the software Isight, multi-objective optimization model is built by adopting non-dominated sorting genetic optimization algorithm (NSGA-II).
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