汽油机加速瞬态工况空燃比优化控制研究
The Study on Gasoline Engine Acceleration Transient Air-fuel Ratio Optimal Control System

由于氧传感器反馈信号存在一定的延时，导致常规反馈空燃比控制存在时滞现象，造成汽油机加速瞬态工况燃烧性能、动力性能与排放性能恶化。为了使加速瞬态工况空燃比能快速稳定在理论空燃比，基于汽油机加速瞬态工况空燃比控制基本策略，提出一种基于BP神经网络控制器（预估NNI辨识器）和基于径向基函数神经网络控制器（RBF-NNC控制器）组成的采用混沌优化算法的复合神经网络空燃比控制系统，并进行计算机仿真验证。结果表明：该优化控制系统可增强汽油机加速瞬态工况空燃比实时性控制与精度，确保发动机实际空燃比稳定在理论空燃比控制范围内，有效解决氧传感器信号传输的迟滞性问题。
Because of the time delay in oxygen sensor feedback signal, the conventional air-fuel ratio feedback control has a time lag, which leads the deterioration of engine combustion performance includeing the acceleration transient combustion performance, power performance and exhaust emissions performance. In order to make the air-fuel ratio stay stably and rapidly in the theoretical air-fuel ratio in the acceleration transient conditions, based on the control strategy of the gasoline engine acceleration transient air-fuel ratio, the composite neural network air-fuel ratio control system was designed on the basis of the BP neural network controller (NNI identification) and based on the RBF neural network controller (NNC controller) with chaotic optimization algorithm and then computer simulation was conducted. The results show that the optimization control system can enhance the real-time feature and accuracy of the acceleration transient air-fuel ratio of the gasoline engine, and stablize the air-fuel ratio in the theoretical value in acceleration transient conditions, and thus solve the problem of hysteresis in signal transmission effectively