Lei, Y., Liu, H., Qiu, J., Zhang, J. et al., "Starting Quality Assessment and Optimization for Automated Manual Transmission," SAE Technical Paper 2012-01-0059, 2012, doi:10.4271/2012-01-0059.
A good starting quality for AMT (Automated Manual Transmission) vehicles means that the vehicle is started quickly and smoothly on the premise of protecting powertrain system. The starting quality is closely related to the vehicle ride comfort and the service life of powertrain system. In order to improve the starting quality, a good idea is evaluating the starting process firstly and then optimizing the control strategy. However this method has two problems to be solved. The first one is how to define a series of objective criterions to judge the starting quality, and the other is how to select a suitable algorithm to optimize the starting control.This paper focuses on the starting quality assessment and optimization of AMT vehicles. First, the assessment criterions for starting quality are defined in detail from the control point of view and a corresponding assessment system is created. The AHP (Analytic Hierarchy Process) methodology is used to determine the weights of assessment criterion. An AMT vehicle simulation model developed in MATLAB/Simulink environment is built for assessment system testing and starting control optimization. Through the co-simulation and calculation of AMT vehicle model and assessment system, the starting control targets, i.e. the expected control ranges of assessment criterions, are obtained. These targets can provide references and guidance for the next step optimization work. Secondly, a fuzzy logic based on starting control strategy is optimized using multi-objective genetic algorithm by selecting the highest level starting quality as the optimization target. The control of both clutch engagement rate and engine throttle opening is optimized and the optimal solution set for fuzzy control rules is obtained. Finally, the simulation results show that the starting quality of AMT vehicle is effectively improved after optimization.