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For the purpose of lessening fuel consumption, engine noise, shift jerk and clutch friction work in the shift process of Automatic Mechanical Transmission (AMT), a fuzzy-bang bang dual mode control strategy for engine rotate speed is put forward in this paper, which takes the advantages of time optimal control and fuzzy control. The combined control strategy is applied to the shift process control of AMT test minibus named SC6350 and proved to be successful by the experimental results.

For the vehicle equipped with stepped automatic transmission (SAT) that has a fixed number of gears, gearshift schedule is crucial to improve the comprehensive performance that takes into account power performance, fuel economy, and driver’s performance expectation together. To optimize and individualize the gearshift schedule, an optimization method and an improved performance evaluation approach for multi-performance gearshift schedule were proposed, which are effective in terms of reflecting the driver's expectation on different performance. However, the proposed optimization method does not consider the influence of the road slope on the comprehensive performance. As the road slope changes the load of vehicle that is different from the load when a vehicle runs on a level road, the optimized gearshift schedule without considering road slope is obviously not the optimal solution for a vehicle equipped with SAT when it runs on ramp.

Precise control of the pressure of hydraulic oil acting on the dual clutches plays a crucial role during the gear-shift process of wet-type dual clutch transmission (DCT) to implement power shift (i.e., torque-interruption-free gear-shift) and to improve shift quality. Firstly, the hydraulic control system for the dual clutches of DCT were developed, based on that, the dynamic model of the hydraulic control system was built that was further integrated into a dynamic model of wet-type DCT. Secondly, the influence of oil pressure on evaluation indices for the gear-shift process such as shift jerk and friction work were discussed theoretically, and the determinant principle of the target oil pressure of dual clutches during both up- and downshift processes was discussed, a PID controller and a fuzzy controller were also designed respectively to trace the oil target pressure of dual clutches during the gear-shift process of DCT.

Shift schedule determines the gear-shift timing of stepped automatic transmissions that directly affects the power performance, fuel economy, and emission of vehicle. Under the circumstance with ever increasing concerns about the issues of energy saving and environment protection, an optimized shift schedule that could make the powertrain system provide sufficient power with minimum fuel consumption and less emission has been becoming a very critical factor to improve the overall performance of vehicles equipped with stepped automatic transmission. Traditional methods usually only consider a certain unique performance index, such as power or economical performance, in a certain shift schedule, i.e., using one unique performance as optimization objective for one shift schedule.

To reach the goal of optimal performance match between engine and transmission, the dynamic characteristics of engine should be taken into consideration. In the paper, the dynamic torque and fuel consumption models of engine, described by a multi-layers feed forward neural network, were established. Based on that, the methods used to calculate the optimal dynamic and economical shift schedules with dynamic 3-parameters were put forward. The shift schedule with dynamic 3-parameters based on neural network model is proven to be superior to the shift schedule with only 2-parameters in both dynamic performance and fuel economy by the test.

To further enhance the comprehensive performance of multi-speed battery electric vehicles (MSBEVs) and meanwhile represent the driver’s expectation on performance, we need to consider the power performance, energy economy and driver’s intention together in the optimization of gearshift schedule. An optimization approach for personalized optimal gearshift schedule (POGS) for MSBEVs is put forward to tackle this issue. A quantification method for driver’s intention based on fuzzy neural network is proposed at first, which takes velocity, strength of accelerator pedal and its change rate as input, and takes driver’s expectations on performance as output. The optimization problem for POGS is then formulated with comprehensive evaluation function as goal, in which the driver’s expectations on performance are used as weights of sub-objective functions corresponding to the power performance and the energy economy, respectively.

Gearshift schedule of stepped automatic transmission (SAT) determines the timing when the gearbox should be shifted from a certain gear position to an adjacent one, which directly affects the performance of complete vehicle. To optimize the comprehensive performance considering power performance, fuel economy, and driver’s performance expectation, the formulation of gearshift schedule needs to take into account a number of factors such as the expression of different performance indices, the identification of driver’s intention on each sub-performance, and the adaption to driving conditions especially the road slope and curve. Based on our previous work, this investigation is focused on the adaptability of the gearshift schedule to curves of the road that could ensure the safety of vehicle and meanwhile maintain an optimal comprehensive performance reflecting a specific driver’s performance expectation.