车用并联混合动力系统瞬态过程控制技术研究
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摘要
混合动力电动汽车开始走向产业化的时期,对其控制策略的研究无疑具有重大现实意义。控制策略的研究手段包括仿真、控制原型开发、硬件在环仿真和系统性能测试。本文通过对各种混合动力系统的共性分析,提出了混合动力系统控制策略开发平台的框架,给出了混合动力系统各个功能模块在控制策略开发的不同阶段可采用的形态以及他们之间的连接关系。为了拓展混合动力控制策略仿真的设计空间,设计了统一化模型接口,提出了基于神经网络的发动机缩放建模方法,并通过实验证明了该建模方法能够达到仿真优化需要的精度。
基于dSPACE系统和发动机动态试验台架,采用模块化和分层设计方法,设计了测试系统的功能模块,部分功能模可实现仿真形态和实物形态置换组合,以满足不同测试的需要,实现了系统模块组合的柔性化。设计完成了系统各种信号协调连接,完成了dsPACE系统、测功机系统和混合动力总成的集成。在所设计的测试平台上进行了并联混合动力测试,实验表明测试平台能实现循环工况模拟、再生制动控制、模式切换控制、换挡控制等过程的测试,测试平台达到了预期的测试功能,为并联混合动力瞬态过程控制技术研究奠定了实验基础。
并联混合动力能量管理和瞬态过程动力控制都需要发动机的实时转矩。本文通过发动机自动化测试,建立了发动机瞬态转矩的查表模型、神经网络拟合模型,并提出了基于神经网络的发动机平均值模型。对三者的实验验证表明,它们都能达到一定的转矩估计精度。但前两种模型的适应性较差,而基于神经网络的平均值模型根据实时测得的进气压力和喷油流量进行转矩估计,具有更好的适应性,也能对节气门变化率不高时的发动机动态转矩进行估计。
本文提出了基于模型预测的电机调速闭环控制策略,用于模式切换控制,它不依赖于对发动机瞬态转矩的精确估计,比单纯根据估计的发动机转矩进行电机转矩补偿控制具有更好的控制鲁棒性。仿真和实验表明所提出的控制策略能够有效降低混合动力模式切换过程中的输出转矩和转速波动,实现模式的平稳切换。该控制策略适用与普通并联混合动力,也适用于plug-in混合动力。
提出了行星齿轮机械变速器方案,通过去除液力自动变速器的变矩器形成的机械自动变速器具有更高的传动效率,同时也保留了其换挡操作的方便性。分析了行星齿轮机械变速器在并联混合动力系统中应用的可行性,对其进行了换挡过程的动力学建模,提出了电机调速主动同步的控制策略,对变速器的加、减挡过程进行了仿真研究,结果表明所提出的电机调速主动同步换挡控制策略能有效降低换挡过程中变速器输出转矩的波动,实现平顺换挡。
With the advent of mass-producing of hybrid electric vehicles (HEV), studying the control strategy of HEV is significance. Simulation, prototype development, hardware-in-the-loop simulation and system bench test are emploied to address the HEV control problem. In this paper, a platform framework was presented for the development of HEV control strategy by abstracting the essential factors of the HEV system. The system was modularized, the states of the modules and their relationship for different developing stage was described. To explore a large design space for HEV, a universal interface definition for Meta-Model was designed, and a neural network based scaling modeling method for engine and electric machine was proposed. Bench test indicated that the scaling model can satisfy the requirement for simulation.
The functional modules of the HEV test system are designed with modularization and hierarchical method. Virtual parts or physical parts are optional to make up various types of test systems, so the system is flexibility to satisfy different of control strategy development purpose. The designed test system can implement the regeneration braking test of HEV. Proper interfaces were designed to integrate the dSPACE system, dynamometer system and hybrid powertrain. Some tests were implemented on the designed test system. The functions of duty cycle simulation, regenerative brake test, HEV mode switch control test and gear shift control test were validated. The test system meet the expected functions, this made a foundation for the study of the transient process control in this paper.
For either energy management or transient process control, it is essential to obtain the torque of the engine. Based on automatic test data, a look-up-table model and neural network model were constructed. This paper comes up with a new type of neural networks based mean value engine model. Experiments results show that these three types of engine models all have certain accuracy for engine torque estimation, but the repeatability of the former two types of model is not steady. The neural network based mean value engine model observe the engine torque by measuring intake pressure and fuel injector flow rate, it has more better robustness and can feedback the transient engine torque if the change rate of throttle is not too high.
For traditional HEV as well as Plug-in HEV, it is very important to have good mode switch and gear shift process. This paper come up with a mode switch control strategy of model-predictive based motor speed regulation, it dose not depend on the accurate engine torque estimation and has better robustness than the only engine torque based torque compensation strategy. The simulation and test results testified that the proposed control strategy can effectively suppress the oscillation of output torque of the parallel hybrid powertrain, and realized a smooth mode switch.
In order to address the gear shifting control problem, a planetary gearing automatic mechanical transmission (PGAMT) was proposed. The torque converter of a hydraulic automatic transmission was removed to form a PGAMT, which transmission efficiency was improved without sacrificing the convenience of the gear shifting. This paper analyzed the operation conditions required for PGAMT in the parallel hybrid powertrain, modeled the dynamic of the PGAMT, proposed a gear shifting control strategy that use the electric motor as the actuator to actively synchronize clutch disks to realize clutch-to-clutch gear shifting, simulated the process of up shift and down shift. The simulation results indicate that the active synchronizing by motor shift control strategy can effectively reduce the oscillation of the output torque of the transmission during the course of gear shifting.
基于dSPACE系统和发动机动态试验台架,采用模块化和分层设计方法,设计了测试系统的功能模块,部分功能模可实现仿真形态和实物形态置换组合,以满足不同测试的需要,实现了系统模块组合的柔性化。设计完成了系统各种信号协调连接,完成了dsPACE系统、测功机系统和混合动力总成的集成。在所设计的测试平台上进行了并联混合动力测试,实验表明测试平台能实现循环工况模拟、再生制动控制、模式切换控制、换挡控制等过程的测试,测试平台达到了预期的测试功能,为并联混合动力瞬态过程控制技术研究奠定了实验基础。
并联混合动力能量管理和瞬态过程动力控制都需要发动机的实时转矩。本文通过发动机自动化测试,建立了发动机瞬态转矩的查表模型、神经网络拟合模型,并提出了基于神经网络的发动机平均值模型。对三者的实验验证表明,它们都能达到一定的转矩估计精度。但前两种模型的适应性较差,而基于神经网络的平均值模型根据实时测得的进气压力和喷油流量进行转矩估计,具有更好的适应性,也能对节气门变化率不高时的发动机动态转矩进行估计。
本文提出了基于模型预测的电机调速闭环控制策略,用于模式切换控制,它不依赖于对发动机瞬态转矩的精确估计,比单纯根据估计的发动机转矩进行电机转矩补偿控制具有更好的控制鲁棒性。仿真和实验表明所提出的控制策略能够有效降低混合动力模式切换过程中的输出转矩和转速波动,实现模式的平稳切换。该控制策略适用与普通并联混合动力,也适用于plug-in混合动力。
提出了行星齿轮机械变速器方案,通过去除液力自动变速器的变矩器形成的机械自动变速器具有更高的传动效率,同时也保留了其换挡操作的方便性。分析了行星齿轮机械变速器在并联混合动力系统中应用的可行性,对其进行了换挡过程的动力学建模,提出了电机调速主动同步的控制策略,对变速器的加、减挡过程进行了仿真研究,结果表明所提出的电机调速主动同步换挡控制策略能有效降低换挡过程中变速器输出转矩的波动,实现平顺换挡。
With the advent of mass-producing of hybrid electric vehicles (HEV), studying the control strategy of HEV is significance. Simulation, prototype development, hardware-in-the-loop simulation and system bench test are emploied to address the HEV control problem. In this paper, a platform framework was presented for the development of HEV control strategy by abstracting the essential factors of the HEV system. The system was modularized, the states of the modules and their relationship for different developing stage was described. To explore a large design space for HEV, a universal interface definition for Meta-Model was designed, and a neural network based scaling modeling method for engine and electric machine was proposed. Bench test indicated that the scaling model can satisfy the requirement for simulation.
The functional modules of the HEV test system are designed with modularization and hierarchical method. Virtual parts or physical parts are optional to make up various types of test systems, so the system is flexibility to satisfy different of control strategy development purpose. The designed test system can implement the regeneration braking test of HEV. Proper interfaces were designed to integrate the dSPACE system, dynamometer system and hybrid powertrain. Some tests were implemented on the designed test system. The functions of duty cycle simulation, regenerative brake test, HEV mode switch control test and gear shift control test were validated. The test system meet the expected functions, this made a foundation for the study of the transient process control in this paper.
For either energy management or transient process control, it is essential to obtain the torque of the engine. Based on automatic test data, a look-up-table model and neural network model were constructed. This paper comes up with a new type of neural networks based mean value engine model. Experiments results show that these three types of engine models all have certain accuracy for engine torque estimation, but the repeatability of the former two types of model is not steady. The neural network based mean value engine model observe the engine torque by measuring intake pressure and fuel injector flow rate, it has more better robustness and can feedback the transient engine torque if the change rate of throttle is not too high.
For traditional HEV as well as Plug-in HEV, it is very important to have good mode switch and gear shift process. This paper come up with a mode switch control strategy of model-predictive based motor speed regulation, it dose not depend on the accurate engine torque estimation and has better robustness than the only engine torque based torque compensation strategy. The simulation and test results testified that the proposed control strategy can effectively suppress the oscillation of output torque of the parallel hybrid powertrain, and realized a smooth mode switch.
In order to address the gear shifting control problem, a planetary gearing automatic mechanical transmission (PGAMT) was proposed. The torque converter of a hydraulic automatic transmission was removed to form a PGAMT, which transmission efficiency was improved without sacrificing the convenience of the gear shifting. This paper analyzed the operation conditions required for PGAMT in the parallel hybrid powertrain, modeled the dynamic of the PGAMT, proposed a gear shifting control strategy that use the electric motor as the actuator to actively synchronize clutch disks to realize clutch-to-clutch gear shifting, simulated the process of up shift and down shift. The simulation results indicate that the active synchronizing by motor shift control strategy can effectively reduce the oscillation of the output torque of the transmission during the course of gear shifting.
引文
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