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As a auxiliary braking device in vehicle’s downhill process, parallel hydraulic retarder has strict requirements for its rapidity of response performance and accuracy of braking torque. The parallel hydraulic retarder uses high-pressure gas as the control medium, which pushes the oil into the working chamber through the high-speed on/off valve. Because the oil filling process of the chamber is an indirect process, the complicated gas–liquid movement during the oil filling period affects the accuracy and response of the braking process. In this paper, the mechanical characteristics of high-speed on/off valve had analyzed by computational fluid dynamics. The oil filling system’s characteristics has analyzed, which had verified by experimental data. Compared with the three dimensional method to directly analyze the response process of the oil charging and discharging system, it has the characteristics of simplicity and fast calculation.The modeling method used in this paper is mainly suitable for hydraulic system which uses air pressure and liquid as control medium. This integration model can obtain the characteristics of valve group more accurately and has certain novelty rather than Theoretical formula calculation. Then the influence of different control pressure and input speed on transient braking response has discussed and analyzed. The results has showed that the shortest opening response time is 1.49 s when the control pressure is 3.2 bar. With the decrease of the oil amount and speed, the oil-discharging response time increases gradually. When the speed is 1800 rpm and the liquid filling rate is 25 %, the oil discharge time reaches 5.48 s.

The main purpose of this paper is to explore the importance of external flow field circulation of hydraulic torque converter assembly in analysis. Compared with simply considering the internal flow field characteristics, it has influence on the internal flow field analysis, external characteristics and structural stress of hydraulic torque converter assembly. This paper models the flow path of the torque converter with different Schemes, the flow field pressures distribution on the impeller are analysed using computational fluid dynamics method (CFD). Scheme A adopts the traditional idea, which simply considering the influence of internal flow field on the performance. Scheme B contacts the external flow field especially including the auxiliary cavity, and comprehensively studies the influence of it on the performance. The results show that with the addition of an auxiliary chamber, the overall flow field pressure of the torque converter is lower than that without the auxiliary chamber. The external characteristics of the torque converter assembly were tested on experiment equipment, which has been verified that the CFD simulation results with the addition of the auxiliary chamber are closer to the experiment data, proving the accuracy of the method for the pressure simulation of flow field. On this basis, the stresses and deformations of the torque converter considering the auxiliary fluid chamber are compared and analysed in relation to the displacement limitations of the impellers. The results show that the maximum stress in the turbine is reduced by 57%–12% compared to the scheme A without considering the auxiliary fluid. In the case of special operating condition, the maximum stress was 137.06 MPa before considering the auxiliary fluid, while the maximum stress was 60.625 MPa after considering the auxiliary fluid, and the reduction is 57%. The effects of input speed, speed ratio and impeller structure on the stress and deformation were also analysed, and the results show that the impeller structure and input speed have a great influence on the stress and deformation.

When launching a heavy-duty vehicle, torque and position control during automatic clutch engagement is critical, and the driver’s intention to launch and changes in the vehicle’s launching resistance make clutch control more complex. This paper analyses the automatic engagement process of automated mechanical transmission (AMT) clutches and proposes an optimal control of the clutch torque for launching heavy-duty vehicles. Firstly, a fuzzy neural network (FNN)-based vehicle launching states recognition (LSR) system is designed for distinguishing the driver’s launching intention and the vehicle’s launching equivalent moment of resistance. Secondly, jerk, friction work, and launching reserve power are taken as the performance indexes for clutch torque optimization, the weight coefficients of each performance index are adjusted according to the LSR results, and the optimal clutch torque is solved by using the minimum value principle based on the shooting method. Finally, simulations and tests are conducted to validate the strategy of optimizing clutch torque, and the impact of torque optimization on the position change during the engagement process is analyzed. The results indicate that under different driver’s intentions, vehicle masses, and road gradient conditions, the jerk, friction work, and slipping time of heavy vehicles during the launching process are improved by applying the optimization strategy.

As an essential part of the transportation industry, it is necessary to reduce the fuel consumption of commercial vehicles from the perspective of the environment and economy. Previous studies have shown that optimizing the gear sequence can reduce vehicle fuel consumption. This paper presents a gear decision method based on predictive road information. Under the model predictive control framework, the dynamic programming algorithm is used to solve the multi-objective optimization problem of gear decision. To solve the problem of the long calculation time of the dynamic programming algorithm, the nonlinear optimization algorithm is used to optimize the dynamic programming sub-problem, and the optimal gear sequence of fuel consumption is obtained. The final optimized gear sequence is obtained through the dynamic programming algorithm. The simulation analysis of the proposed gear shift decision method shows that the gear shift decision method can effectively reduce fuel consumption under fixed working conditions. Compared with the economic shift schedule, the fuel consumption is reduced by 5%, and the computing speed is improved compared with the dynamic programming algorithm.