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Research On Torque-based Control For Tracked Heavy-Duty Vehicle Powertrain Device

Posted on:2016-11-07Degree:DoctorType:Dissertation
Country:ChinaCandidate:G LiFull Text:PDF
GTID:1222330476450717Subject:Power Machinery and Engineering
Abstract/Summary:PDF Full Text Request
Vehicle powertrain device integrated control technology, which is critical to vehicle dynamic matching and overall performance, stands for the direction of future powertrain development. Torque-based control strategy is applied and research extensively for the standard system architecture and torque interface. But the integrated control technology of heavy tracked vehicle is still in the inception phase. In order to improve tracked vehicle performance and reliability, shorten development cycle, the studies on vehicle integrated control under the torque architecture for tracked vehicle were presented. In this paper, DEUTZ BF6M1015 turbocharged diesel engine and a type of tracked vehicle are selected as the research object, and the torque-based control strategy will be designed.For the system analysis and control function designing, the dynamic simulation model of tracked vehicle powertrain has been built. Through a typical case analysis of dynamic simulation, the main control problems of tracked vehicle have been obtained. The control structure and basic control function are designed. It mainly includes: the calculation of dynamic torque demand, torque coordination and parts management, indicated torque control method. The system function designing provides a foundation for the following research.Considering the drastic change of the tracked vehicle torque demand, the dynamic indicated torque control method for turbocharged diesel engine model has been proposed, which is based on the dynamic torque prediction model. The basic torque value can be obtained by steady-state torque model, and then the dynamic torque coefficient can be calculated according to the difference between steady-state and dynamic operation condition. Ultimately dynamic indicated torque can be obtained by modifying the basic torque with the difference coefficient. Base on this prediction model, the control MAPs have been made by the secant method which describes the relation between target torque and fuel mass. And the experiment results show that this method can improve the control accuracy of the dynamic indicated torque.Based on the crankshaft dynamics analysis, the indicated torque estimation method for turbocharged diesel engine model has been proposed. First the calculation formula of average indicated torque has been derived from the 1 order amplitude and phase of cylinder pressure. Then the linear relationship between 1 order cylinder pressure amplitude and firing order engine speed amplitude has been obtained by experimental study. Meanwhile, 1 order cylinder pressure phase can be calculated by intake pressure, 1 order cylinder pressure amplitude and 1 order combustion cylinder pressure phase. Finally by using DSP system, the real-time calculation of firing order engine speed amplitude can be realized. Experimental results show that the relative average estimation error is accepted in the rapid torque increase and decrease process.After the designing of torque control and torque estimation, the speed control strategy research has been conducted under the torque architecture for tracked vehicle. Based on the torque estimation,the load estimation algorithm is designed and the estimation precision validation is performed in steady and transient conditions. In order to improve load disturbance rejection and speed control effect, the feedforward-feedback speed control and model predictive speed control considering driving intention have been proposed under the torque-based architecture. Finally, with the tracking characteristics of pedal-speed improved, unexpected shift of the tracked vehicle can be reduced in a driving cycle for tracked vehicle.
Keywords/Search Tags:Tracked vehicle, turbocharged diesel engine, torque-based control, torque estimation, speed control
PDF Full Text Request
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