A theoretical study on the high-speed electric tracked vehicle mobility

Abstract

The article deals with the problem of the characteristics selection for the electric motors of the drivetrains of the high-speed tracked vehicles with individually driven sprockets. The existing method of the tracked vehicle cornering dynamics analysis is not suitable for the analysis of the motion at the speeds near to the critical speeds in the skidding mode. The authors offer a method for improving the accuracy of the existing analytical dependencies by the use of neural network. The above-mentioned improvements provide estimation of the limit values of the required traction forces on the sides of the vehicle but they do not allow gathering statistical data on the electric motor operating conditions of short and long duration during the vehicle operation. The authors offer to solve this problem by means of a driving simulation complex. The complex provides simulation of the tracked vehicles driving along stochastic routes in real time mode and collection of the stochastic data on the electric motor loads.

Series-Hybrid Powertrains: Advancing Mobility Control in Electric Tracked Vehicle Technology

“…Summary of the corresponding study is presented in Figure 2. In their review of electric tracked vehicle mobility, Kotiev et al address the complexities of achieving balanced torque in high-speed scenarios, particularly through individual drives on each sprocket [9]. Traditional methodologies are determined insufficient for accurate analysis, causing the authors to incorporate neural networks and simulation tools to better predict the thrust requirements for various steering conditions.…”

“…Overall, a review of the literature indicates that steering ability could potentially be synthesized and augmented through the application of either advanced closed-loop control software or simpler software assisted by an optimized transmission mechanism. This In their review of electric tracked vehicle mobility, Kotiev et al address the complexities of achieving balanced torque in high-speed scenarios, particularly through individual drives on each sprocket [9]. Traditional methodologies are determined insufficient for accurate analysis, causing the authors to incorporate neural networks and simulation tools to better predict the thrust requirements for various steering conditions.…”