首页> 外文OA文献 >A Virtual In-Cylinder Pressure Sensor Based on EKF and Frequency-Amplitude-Modulation Fourier-Series Method
【2h】

A Virtual In-Cylinder Pressure Sensor Based on EKF and Frequency-Amplitude-Modulation Fourier-Series Method

机译:基于EKF和频率振幅调制的虚拟缸压压力传感器

代理获取
本网站仅为用户提供外文OA文献查询和代理获取服务,本网站没有原文。下单后我们将采用程序或人工为您竭诚获取高质量的原文,但由于OA文献来源多样且变更频繁,仍可能出现获取不到、文献不完整或与标题不符等情况,如果获取不到我们将提供退款服务。请知悉。

摘要

As a crucial and critical factor in monitoring the internal state of an engine, cylinder pressure is mainly used to monitor the burning efficiency, to detect engine faults, and to compute engine dynamics. Although the intrusive type cylinder pressure sensor has been greatly improved, it has been criticized by researchers for high cost, low reliability and short life due to severe working environments. Therefore, aimed at low-cost, real-time, non-invasive, and high-accuracy, this paper presents the cylinder pressure identification method also called a virtual cylinder pressure sensor, involving Frequency-Amplitude Modulated Fourier Series (FAMFS) and Extended-Kalman-Filter-optimized (EKF) engine model. This paper establishes an iterative speed model based on burning theory and Law of energy Conservation. Efficiency coefficient is used to represent operating state of engine from fuel to motion. The iterative speed model associated with the throttle opening value and the crankshaft load. The EKF is used to estimate the optimal output of this iteration model. The optimal output of the speed iteration model is utilized to separately compute the frequency and amplitude of the cylinder pressure cycle-to-cycle. A standard engine’s working cycle, identified by the 24th order Fourier series, is determined. Using frequency and amplitude obtained from the iteration model to modulate the Fourier series yields a complete pressure model. A commercial engine (EA211) provided by the China FAW Group corporate R&D center is used to verify the method. Test results show that this novel method possesses high accuracy and real-time capability, with an error percentage for speed below 9.6% and the cumulative error percentage of cylinder pressure less than 1.8% when A/F Ratio coefficient is setup at 0.85. Error percentage for speed below 1.7% and the cumulative error percentage of cylinder pressure no more than 1.4% when A/F Ratio coefficient is setup at 0.95. Thus, the novel method’s accuracy and feasibility are verified.
机译:如在监测发动机的内部状态的关键和重要的因素,气缸压力主要用于监测燃烧效率,以检测发动机的故障,并计算发动机动力学。虽然侵入式气缸压力传感器有了很大的提高,已经批评研究者高成本,低可靠性和寿命短,由于严重的工作环境。因此,意在低成本,实时的,非侵入性,和高的精度,本文提出的气缸压力的识别方法也被称为虚拟缸压力传感器,涉及频幅度调制傅立叶级数(FAMFS)和延伸期卡尔曼滤波器优化(EKF)发动机模型。本文建立了基于燃烧节能的理论和法律迭代速度模型。效率系数被用来表示发动机的运转状态从燃料到运动。与节气门开度值和曲轴负荷相关联的迭代速度模型。 EKF的用于估计本次迭代模型的最优输出。速度迭代模型的最优输出利用来分别计算气缸压力周期到周期的频率和幅度。一个标准的发动机的工作周期,由24阶傅里叶级数确定,确定。使用频率和来自迭代的模型幅值获得调制傅立叶级数产生一个完整的压力模型。由中国一汽集团企业R&d中心提供的市售发动机(EA211)被用来验证方法。测试结果表明,该新方法具有较高的精确度和实时能力,具有用于速度的误差百分比低于9.6%和气缸压力的累积误差百分比小于1.8%时,A / F比率系数是设置在0.85。对于速度以下1.7%和气缸压力的累积误差百分比不大于1.4%的误差率,当A / F比率系数是设置在0.95。因此,所述新颖的方法的准确性和可行性进行验证。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
代理获取

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号