【作者】 王莉；

【导师】 刘鲁源；

【作者基本信息】 天津大学 ， 电力电子与电力传动， 2004， 博士

【摘要】 汽油机采用电控技术已经成为节能和控制排气污染的必不可少的技术手段。准均质稀混合气燃烧新技术可以充分发挥稀薄燃烧的优势,有利于降低发动机的油耗和排放,但是对发动机控制系统的要求更高。本文针对稀薄燃烧发动机的特点,提出了一个准均质稀薄燃烧发动机模型。该模型以平均值模型为基础,包括进气回路子模型、燃油回路子模型和动力输出子模型三部分,为准均质稀薄燃烧发动机的空燃比控制方案和采用浓-稀转换的方式进行稀薄燃烧发动机排气后处理的控制方案提供了依据。为了满足稀薄燃烧发动机对空燃比控制的特殊要求,本文将滑模变结构控制和神经网络理论应用于稀薄燃烧发动机的空燃比控制,提出了滑模-神经网络稀薄燃烧发动机空燃比控制策略。采用以反馈为主的滑模变结构方法控制“准稳态”的空燃比,其变结构控制器的设计采用本文所提出的模糊趋近律方法,采用神经网络构造进气量观测器和瞬态燃油补偿。本文提出了一个稀薄燃烧发动机综合控制方案以降低准均质稀薄燃烧发动机排放。该方案针对NOx 吸附催化转化器的工作原理及其对控制系统的特殊要求,采用滑模-神经网络策略控制喷油脉宽、基于稀薄燃烧发动机模型的转换MAP 图加自学习的方式控制节气门开度、以及基于最优扭矩的爆震闭环控制方式控制点火提前角。试验证明该方案可以达到将转速和扭矩的波动控制在较小范围内的目的,学习控制在一定的转换过程之后进一步降低了转速和扭矩的波动,优化了发动机的浓稀转换过程。针对发动机控制试验的要求,自行设计硬件和软件,研制开发了一套功能完善的稀薄燃烧发动机电控开发系统,并以此为平台,在丰田8A 发动机上进行了稀薄燃烧发动机空燃比控制试验和NOx 排放综合控制试验。试验表明采用滑模-神经网络策略对稀薄燃烧发动机空燃比进行控制可以将过渡过程的空燃比超调降低到0.2 个空燃比单位,标定加迭代学习的控制方案控制NOx 吸附-还原催化转化器的浓稀转换过程是切实可行的方案。所开发的电控系统工作稳定可靠,完全满足本课题的应用要求。更多还原

【Abstract】 It is necessary to apply electronic control technology to the engine in order to economize on energy and reduce the emission pollution. The new technology, quasi-homogeneous lean burn, can give full play to the advantage of lean burn, and thus help to reduce the fuel consumption and emission of the engine. However, higher requirements are raised for the engine control system. The quasi-homogeneous lean burn engine model is presented in this paper for the characteristics of the lean burn engine. On the basis of the mean value engine model, this lean burn engine model can be built up of three subsystems: manifold air mass flow, fuel vapor and fuel film, and crank shaft and loading. Thus scientific basis is provided for the air-fuel ratio (AFR) control scheme for the quasi-homogeneous lean burn engine and for the emission reduction control scheme for the quasi-homogeneous lean burn engine by AFR switching. To meet the special requirement of the air-fuel ratio control for lean burn engine, a sliding mode-neural network control scheme for the air-fuel ratio of the quasi-homogeneous lean burn engine is presented in this paper based on the quasi-homogeneous lean burn engine model. In this scheme, the sliding variable structure control strategy, in which the feedback control is its key idea, is designed using fuzzy exponential approach and adopted to control the air-fuel ratio under the condition of quasi-steady state. At the same time, the neural network method is applied to build the intake air flow observer and realize the instantaneous fuel compensation. To reduce the emission of the quasi-homogeneous lean burn engine, a comprehensive control scheme for the quasi-homogeneous lean burn engine is proposed in this paper. According to the working principle of NOx storage-reduction catalyst converter and its special demand for the control system, the sliding mode-neural network control scheme is adopted to control the injection pulse width, while the MAP converting method combined with online correction is adopted to realize the control of the throttle opening and the torque-based knocking closed-loop control scheme is adopted to control the spark ignition timing. The experiments show that by this scheme, the fluctuation of the output power can be confined to a smaller range, and it can be further reduced after certain transformation by the learning control. Thus the AFR step process of the engine can be optimized. To satisfy the special requirements of control experiments of gasoline engine, the author has developed an electronic control system suitable for lean burn gasoline engine with the self-developed hardware and software. The quasi-homogeneous lean burn engine air-fuel ratio control experiments and NOx emission comprehensive control experiments are carried out on a Toyota 8A gasoline engine with this system. By the experiments results, it can be shown that applying sliding mode-neural network scheme to control the air-fuel ratio of the quasi-homogeneous lean burn engine, the overshoot can be reduced to 0.2 AFR unit. At the same time, the combination of calibration and iterative leaning control scheme is practicable to control the AFR step process of a lean burn engine with the NOx storage-reduction catalyst. The results also show that the electronic control system has reliable performances and can completely fulfill the requirements of the project.更多还原