Self-Adapt Slope Gear Shift Strategy For The Electronic Controlled And Electronic Powered AMT

Shift schedule is the key technique and the soul of the AMT, deciding the time to shift. The shift schedule self-adaptability directly influence the power, fuel economy, and driving smoothness. To the present, both double parameter and triple parameter shifting rule are depend upon the designated control parameters and the optimal performance index. To some extend, these two kinds of traditional parameter shifting rules lead to abnormal shifting and shift cycle phenomena. Additionally, the road grade is one of the most difficult point of shift schedule analysis.The AMT self-adaptive ramp shift schedule strategy possess important practical application value to improve automobiles shift schedule self-adaptability. To details, it avoids overheating of the brake drum or brake disc because of the downhill’s continuous braking and partial shift cycle when cars’uphill. Moreover, the AMT ramp shift schedule self-adaptability can help lessen the burden on the driver’s operation and reduce mechanical injuries because of abnormal shifting. Therefore, it is important to analyze the ramp shift schedule self-adaptive control strategy. Based on a practice engineering project, this paper investigated AMT ramp shift schedule self-adaptive strategy based on the fitness of assigned car and AMT. Furthermore, the the content of the paper is as follows:1. Introducing and analyzing the shift schedule self-adaptability theory and the control technology. Coming up with the combined shifting strategy between the self-adaptive control technology and the intelligent control based on the above introduction and analysis.2. The steady engine characteristic function was fitted upon the numbers of the engines. The numerical model, and the simulation model of clutch and Furthermore, the hole vehicle simulation model was established upon the previous models.3.The proposed fuzzy neural control basing on the hole vehicle simulation was simulated and tested. The results of simulation and test suggested that comparing with the previous shifting strategy, the present fuzzy neural controlling shift strategy highlighted its real-time and validity characters.