Likelihood-Based Control of Engine Knock

Jones, James C. Peyton; Spelina, Jill M.; Frey, Jesse

doi:10.1109/tcst.2012.2229280

Cited by 59 publications

(33 citation statements)

References 14 publications

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“…This was strengthened by the evaluation in [20] and will not be further treated here. Given the statistical independence of knock observations, the process can be completely characterized by the uni-dimensional probability density function (PDF) of the process.…”

Section: Engine Knock Characterizationmentioning

confidence: 97%

“…The likelihood-based controller advocated in [20] addresses these issues by adjusting the spark angle only when there is sufficient statistical evidence that a control move is necessary. The magnitude of these adjustments is also scaled according to the likelihood of the observations that are actually recorded from the engine.…”

Section: Likelihood-based Knock Controlmentioning

confidence: 99%

“…The reset cycle count is increased in three stages, after one, two and three spark advances with zero knock, so that the rate of spark advance increases until the first knock event occurs. With this slight modification, the algorithm presented in [19,20] becomes as shown in Algorithm 1.…”

Section: A the Algorithm And Background Theorymentioning

confidence: 99%

“…5. The [20] during test at an engine speed of 1500 rpm, an intake pressure of 120 kPa and compression ratio of 12. parameter choice is the same as the final tuning in [20], p = 0.01, K Adv = 0.3, K Ret = 0.6, Likelihood threshold 0.4, and with reset cycle count after spark advance of 70, corresponding to k 0 = {0, 70, 70, 70} in Algorithm 1. Compared to the conventional controller the knock rate is slightly higher, 1.08% and the spark advance slightly more advanced by 0.14 degrees.…”

Section: B Experimental Evaluationmentioning

confidence: 99%

“…This controller reacts quickly to changes in knock rate while having less cyclic variability compared to the conventional controller, achieving a mean spark advance closer to the knock limit. An alternative stochastic controller using likelihood ratios was presented in [19], and further developed in [20], which has shown good performance in simulation.…”

Section: Introductionmentioning

confidence: 99%

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Tuning and experimental evaluation of a likelihood-based engine knock controller

Thomasson

Eriksson

Lindell

et al. 2013

52nd IEEE Conference on Decision and Control

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Abstract-A new likelihood-based stochastic knock controller, that achieves a significantly improved regulatory response relative to conventional strategies, while also maintaining a rapid transient response is presented. Up until now it has only been evaluated using simulations and the main contribution here is the implementation and validation of the knock controller on a five cylinder engine with variable compression ratio. Furthermore, an extension of the fast response strategy and a re-tuning of the controller is shown to improve performance. The controller is validated with respect to its robustness to changes in engine operating condition as well as compression ratio. The likelihood-based controller is demonstrated in engine tests and compared to a conventional controller and it is shown that it is able to operate closer to the knock limit with less variations in control action without increasing the risk of engine damage.

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Section: Engine Knock Characterizationmentioning

confidence: 97%

Section: Likelihood-based Knock Controlmentioning

confidence: 99%

Section: A the Algorithm And Background Theorymentioning

confidence: 99%

Section: B Experimental Evaluationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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