Optimization of Shift Strategy Based on Vehicle Mass and Road Gradient Estimation

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Abstract
For electrically driven commercial vehicles equipped with three-speed automatic mechanical transmission (AMT), the transmission control unit (TCU) without vehicle mass and road gradient estimation function will lead to frequent shifting and insufficient power during vehicle full-load or grade climbing. Therefore, it is necessary to estimate the mass and road gradient for the electrically driven commercial vehicles equipped with the three-speed AMT, and to adjust the shift rule according to the estimation results. Given the above problems, this paper focuses on the control and development of the electrically driven three-speed AMT and takes the shift controller with the vehicle mass and road gradient estimation as the research goal. The mathematical model and simulation model of vehicle dynamics are established to verify the shift function of TCU. The least squares method and calibration techniques are applied to estimate the vehicle mass and road gradient. According to the estimation results, the existing shift strategy is optimized, and the software-in-the-loop simulation of the transmission controller is carried out to verify the function of the control algorithm software. The hardware-in-the-loop test model is established to verify the shift strategy’s optimization effect, which shortens the controller’s forward development cycle. According to the estimation results of mass and gradient, the error result of the proposed method is controlled within 4.5% for mass and 8.6% for gradient. The experiment verifies that the optimized shift strategy can effectively improve the dynamic performance of the vehicle. The HIL experimental results show that the vehicle can maintain low gear while climbing the hill, and the vehicle speed does not decrease significantly.

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