Modeling and identification of the combustion pressure process in internal combustion engines; 2: Experimental results
- Ohio State Univ., Columbus, OH (United States). Dept. of Mechanical Engineering
- Univ. of Michigan, Ann Arbor, MI (United States). Dept. of Electrical Engineering and Computer Science
In Connolly and Yagle they presented a new model relating cylinder combustion pressure to crankshaft angular velocity in an internal combustion engine, primarily the fluctuations in velocity near the cylinder firing frequency. There are three aspects to this model. First, by changing the independent variable from time to crankshaft angle, a nonlinear differential equation becomes a linear first-order differential equation. Second, a new stochastic model for combustion pressure uses the sum of a deterministic waveform and a raised-cosine window amplitude-modulated by a Bernoulli-Gaussian random sequence, parameterizing the pressure by the sample modulating sequence. This results in a state equation for the square of angular velocity sampled every combustion, with the modulating sequence as input. Third, the inverse problem of reconstructing pressure from noisy angular velocity measurements was formulated as a state-space deconvolution problem, and solved using a Kalman-filter-based deconvolution algorithm. Simulation results in Connolly and Yagle show that the parameterized pressure can be deconvolved at low to moderate noise levels, and combustion misfires detected, all in real time. This paper presents and discusses experimental results that confirm this model, at least at the relatively low-speed, low-to-moderate load operating conditions analyzed. They show that cyclic combustion pressure variation is fairly well modeled and may be directly estimated from angular velocity measurements. Since the experimental data are taken from an actual V-6 automobile engine, and the algorithms are simple enough to be implemented in real time, these results are directly applicable to real-world combustion pressure identification.
- OSTI ID:
- 7046692
- Journal Information:
- Journal of Engineering for Gas Turbines and Power; (United States), Vol. 115:4; ISSN 0742-4795
- Country of Publication:
- United States
- Language:
- English
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