Abstract

For the multi cylinder gasoline engine, the consistency of each cylinder is an important index to affect the emission and the power. In this paper, in order to reduce the air-fuel ratio (A/F) maldistribution of the engine based on the electromagnetic valve train (EMVT), an individual cylinder A/F estimation algorithm is proposed for the individual cylinder A/F control. Based on the analysis of the hybrid and transfer models of the exhaust of each cylinder in steady state, an individual A/F observer is established by using Kalman filter algorithm. Then the unknown parameters in the observer are identified by the differential evolution(DE) algorithm. Only a single wide area exhaust oxygen(UEGO) sensor is needed to identify the unknown parameters and estimate the A/F of each cylinder. The combined simulation of GT-Power and Simulink validates the effectiveness of the proposed estimation approach. The results show that the proposed method can provide good estimation results under steady-state condition.

Highlights

  • air-fuel ratio (A/F) is one of the most important control variables in the electronic control system of engine, and its control precision is closely related to engine power, economy and emission [1,2]

  • This paper focuses on the individual cylinder A/F estimation based on the electromagnetic valve train (EMVT)

  • The EMVT engine is modified on the basis of a 1.8L four-cylinder port-injected gasoline engine with symmetrical exhaust manifolds, and a UEGO sensor is installed at the confluence of the exhaust manifold

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Summary

Introduction

A/F is one of the most important control variables in the electronic control system of engine, and its control precision is closely related to engine power, economy and emission [1,2]. The frequency domain method is to extract the frequency components that coincide with the exhaust frequency in the UEGO sensor signal, and to eliminate the difference between cylinders’ A/F by suppression of these spectral components [4,5,6]. Both time-domain modeling and frequency-domain modeling require installing an UEGO sensor at the exhaust outlet of each cylinder in the process of parameter identification, and have high consistency requirements for the response speed and delay characteristics of each sensor, increasing the cost and complexity of the test.

System Analysis
Exhaust Gas-Mixing Dynamics Model
UEGO sensor model
Uneven generation and transfer model
Establishment of Kalman filter Observer
Parameter identification
Estimation results of Kalman observer
Findings
Conclusion
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