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The pure electric bus with multi gear transmission can effectively improve the acceleration ability and driving range. However， the design of shift schedule is faced with the problems of heavy workload， high cost and over dependence on the experience of calibration engineers. Therefore， a model-based shift schedule design method， which can effectively shorten the development cycle of shift schedule is proposed. Firstly， dynamic programming is used to optimize the shift sequence of vehicles under standard cycle conditions. Then， the shift points obtained are taken as data samples， and the shift schedule that can be directly used in vehicle controller is extracted by cluster analysis method. Finally， the effectiveness of the extracted shift schedule is verified by simulation. The simulation results show that the vehicle using the shift schedule designed in this paper can give consideration to both dynamic and economy. Compared with the original shift schedule， the cycle power consumption can be reduced by 5.51%.

A volumetric Kalman filter estimation algorithm with good real-time accuracy and stability is used to identify the quality of electric bus and road gradient in complex environment. A dynamics model of 4-gear automated mechanical transmission is established, and an economical shift strategy is proposed which is based on the fusion of four parameters: vehicle speed, throttle opening, vehicle quality and road gradient. The simulation results show the identification algorithm proposed can identify vehicle quality and road gradient accurately without adding any sensors. The multi-parameter fusion shifting strategy developed can achieve economical shifting under the condition of guaranteeing vehicle dynamic performance, which can avoid frequent shift, reduce component wear and improve ride comfort to a great extent.

In order to meet the safety requirements of automobile braking, to improve the braking energy recovery rate of pure electric buses and increase their driving range, the maximum regenerative braking force that the motor can provide is used to determine the front and rear wheel friction braking force distribution curve. A parallel regenerative braking control strategy, A, is proposed to make full use of the motor performance. Aiming at the problems of low power density and short cycle life with a single power battery, a composite energy system composed of power batteries and supercapacitors is designed, and an alternative energy control strategy, D, using real-time wavelet transform control is proposed. The required power is decomposed into high-frequency components and low-frequency components by using the wavelet transform control, in which the high-frequency power is borne by the supercapacitor to avoid impact on the power battery. The simulation model was created using MATLAB/Simulink software, and the simulation was carried out under combined cycle conditions to verify the effectiveness of the control strategy. The simulation results showed that compared with the original vehicle control strategy, adopting the A regenerative braking control strategy can reduce the battery SOC drop by 5.15%, increase the relative increase by 47.9%, and improve the braking energy recovery rate. Compared with the traditional logic threshold regenerative braking control strategy, AC, the AD control strategy can effectively reduce the impact of the peak current and high-frequency demands of the power battery on the battery. The maximum output current of the battery was reduced by 39.5%. The decrease in battery SOC decreased by 0.69%, and the relative increase increased by 12.43%. The driving range and braking performance of the vehicle have thus been effectively improved.