Research on Optimal Shift Control Strategy of Two-speed AMT based on Fuzzy Control

Abstract

For a two-speed AMT pure electric commercial vehicle, the pros and cons of the shift control strategy directly determine the overall vehicle performance of the electric vehicle, such as power and economy. This article takes a certain type of commercial pure electric vehicle equipped with a two-speed automatic transmission as the research object, formulates a dynamic shift rule based on the torque map of the motor, structures an economic shift rule based on the efficiency map, and identifies road gradient and Car load quality, comprehensive consideration of the car’s loading quality, road slope, accelerator pedal opening, accelerator pedal opening change rate, vehicle speed and other parameters for optimal shift control strategy formulation. Comparing the dynamic shift strategy with the economic shift strategy, simulation analysis results show that the optimized shift control strategy can meet the requirements of dynamic performance and has the advantages of economy and energy saving.

An Adaptive Shift Schedule Design Method for Multi-Gear AMT Electric Vehicles Based on Dynamic Programming and Fuzzy Logical Control

“…Fuzzy logic control is a robust control method that does not depend on mathematical models. It has been popularly applied to the control strategy of EVs as it can effectively solve the control problem of vehicles under complex working conditions [22,43]. This paper employs the fuzzy logical control method to adjust the velocity of the upshift points and the downshift points based on the DP-based schedule.…”

“…Therefore, the membership function of the load variation, acceleration, and velocity adjustment can be obtained, as shown in Figure 12. In this study, the Mamdani model is utilized to formulate the control rules [43], where there are two fuzzy input variables, (i.e., load variation and acceleration), and each of them has seven subsets. Therefore, a total of 7 × 7 = 49 control rules can be acquired.…”

“…The centroid method is utilized to defuzzify the fuzzy inference result to obtain the exact output value [43]. Hence, the relationship between shift velocity adjustment and vehicle load and acceleration can be acquired, as shown in Figure 13.…”

“…Third, a specific shift schedule with a straightforward control strategy should be more appropriate than a complicated algorithm considering a vehicle processor's computing limits and costs. Inspired by [42,43], a Fuzzy logical-based controller was designed, considering the variation in the vehicle load and acceleration to regulate the gear shift velocity of a predesigned shift map online, which was extracted from the offline DP solution to promote the comprehensive performance of the vehicle in practice.…”