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The ever-growing number of interacting electronic vehicle control systems requires new control algorithms to manage the increasing system complexity. As a result, torque-based control architecture has been popular for its easy extension as the torque demand variable is the only interface between the engine control algorithms and other vehicle control systems. Under the torque-based control architecture, the engine and AT coordinated control for upshift process is investigated. Based on the dynamics analysis, quantitative relationship between the turbine torque of HTC and output shaft torque of AT has been obtained. Then the coordinated control strategy has been developed to smooth the torque trajectory of AT output shaft. The designed control strategy is tested on a powertrain simulation model in MATLAB/Simulink and a test bench. Through simulation, the shift time range in which the engine coordinated control strategy is effective is acquired.

In view of the requirements of torque-based engine control and coordinated control for hybrid powertrain systems during mode switching and shifting, engine torque needs to be known. A framework for torque generated model was established, and the influencing factors of engine effective torque were analyzed. Then steady and transient performance tests of DEUTZ 6V1015 diesel engine were designed in order to get sample data to train ENNs. By use of the trained ENNs the estimations of both steady and transient friction torque and indicated thermal efficiency were completed, results were: the estimation error of friction torque and indicated thermal efficiency was less than 5%. Then the complete torque generated model was established by embedding the trained ENNs, and the estimation of effective torque was done, results were: the estimation error was less than 5%.

In order to improve the anti-disturbance performance of engine-load and the effect on speed control for the diesel engine, the paper presents the fuzzy-PID speed control strategy in the architecture of torque-based control. The engine-load estimation algorithm is designed based on the mean-value-model and crankshaft dynamics model, and the estimation precision is validated by engine test in both steady and dynamic conditions. Through the experiment verification of the diesel engine, the fuzzy-PID control strategy based on load estimation can significantly improve the anti-disturbance performance of engine-load in the speed control.