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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.

To improve the comprehensive performance of vehicles equipped with stepped automatic transmission (SAT), the optimization of gearshift schedule should take into account various performance such as power performance, fuel economy, etc. In addition, the SATs would become more acceptable if the optimized gearshift schedule could also be individualized to reflect the driver’s expectation on vehicle performance to a reasonable extent. For the purpose of ensuring the comprehensive performance and improving the individual-ability (i.e., the ability to adapt to different driver’s performance expectation) of vehicles equipped with SAT, a linear weighted method has been proposed to construct a performance evaluation function, which applies different weights to represent driver’s expectation on performance by using these weights to multiply the normalized value of each sub-performance index.

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 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.