Model-based within-a-cycle estimation of rate shaping for a piezoelectric fuel injector

Shen, Jin; Pietrzak, Bradley W.; Ruikar, Neha; Le, Dat; Shaver, Gregory M.

doi:10.1016/j.conengprac.2014.02.010

Cited by 3 publications

(9 citation statements)

References 14 publications

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“…Additionally, the instantaneous fuel flow rate w stc is measurable in the injector test rig at Purdue, but is useful only for model validation purposes. With this in mind, the state estimator in [8] was designed to provide virtual measurements of all the states as well output fuel flow rate w stc . The lack of true measurements available on-engine makes control design and parameter estimation particularly difficult, and this will be seen later in this paper.…”

Section: B Available Measurementsmentioning

confidence: 99%

“…The state estimator, previously designed in [8], is used here to provide an estimate of the needle lift x 2 . The estimator is based on a simplified version of the injector simulation model in [6], and contains only six states as well as simplifying assumptions about the bulk modulus and density of the fuel in the injector.…”

Section: B State Estimatormentioning

confidence: 99%

“…Furthermore, A 1 (x 2 ) is not a constant parameter since it is a function of the state x 2 , whose values range from zero to saturation over the course of a single boot-shaped injection event. The parameter estimation strategy used to estimate A 1 (x 2 ) was designed with two "tools" in mind: the total injected fuel per cycle measurement, and the state estimator from [8]. The complete strategy is illustrated in Fig.…”

Section: Parameter Estimationmentioning

confidence: 99%

“…In this paper, a model-based parameter estimation strategy for the piezoelectric fuel injector that estimates the injector's needle seat effective area as function of needle lift is outlined. The resulting parameter estimator is used to improve the performance of the state estimator in [8] when the parameters in the state estimator are assumed to contain some initial error. …”

Section: Introductionmentioning

confidence: 99%

“…In addition, model-based fuel flow estimators for both cycle-tocycle and within-a-cycle control were developed in [7] and [8], respectively. In this paper, a model-based parameter estimation strategy for the piezoelectric fuel injector that estimates the injector's needle seat effective area as function of needle lift is outlined.…”

Section: Introductionmentioning

confidence: 99%

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Model-based estimation of piezoelectric fuel injector parameters

Pietrzak

Shaver

2014

2014 American Control Conference

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Fuel injection rate shaping is one path towards cleaner and more efficient diesel engines. Piezoelectrically actuated fuel injectors meet this requirement, but can exhibit improved model-based estimation performance when their internal parameters are estimated on line. To this end, this paper presents an online parameter estimation strategy for a piezoelectric fuel injector that results in improved fuel flow rate estimation when there is assumed to be some initial error in the parameter estimates. In the presence of an initial parameter error of 25%, the parameter estimator improved the model-based prediction of total injected fuel by approximately 10%.

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Section: B Available Measurementsmentioning

confidence: 99%

Section: B State Estimatormentioning

confidence: 99%

Section: Parameter Estimationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Model-based estimation of piezoelectric fuel injector parameters

Pietrzak

Shaver

2014

2014 American Control Conference

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Low-order control-oriented modeling of piezoelectric actuator using Huberian function with low threshold: pseudolinear and neural network models

Corbier

Ugalde

2016

Nonlinear Dyn

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International audienceThis paper presents a new methodology of nonlinear system identification using Huberian function. Pseudolinear and Neural network black box model families are applied to identify a piezoelectric actuator for suspensions and vibration assisted drilling. Huberian function, which is a mixture of L2L2L\₂ and L1L1L\₁ norms with a threshold, is used to estimate a parameters vector in these model families. Pseudolinear black box model with reduced model order and balanced simplicity-accuracy neural network model families are proposed. Moreover, we show the interest to decrease the threshold in the Huberian function by providing efficient models for vibration drilling control. Experimental results are presented and discusse

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Fuel injection rate shaping and its effect on spray parameters in a direct-injection gasoline system

Pielecha

2022

J Vis

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The presented test results contain an analysis of the variable control of fuel flow from high-pressure gasoline injectors. To control such a system, the cRIO 9063 system and NI-driven module were used. This system allows controlling a piezoelectric injector with a time-varying needle height, which affects the time-varying fuel flow during a single-time opening of the injector needle. The tests were carried out in a constant volume chamber with a constant fuel dose (Pinj = 15 MPa and qo = 17.4 mg), with two values of medium back pressure: Pb = 1.0 and 1.5 MPa as well as different injector opening times (resulting from equal doses of fuel). Analyzes of changes in linear and radial fuel spray range as well as the fuel spray volume were made. It has been found that injection rate-shaping allows to control the fuel flow from the injector at a variable needle height. A reduction of the linear range of the spray by 50% and a radial range by 40% compared to conventional settings within a specified time from the start of the injection was achieved. The surface area of the spray is limited by a maximum of 60% compared to the settings at the maximum control voltage. The use of injection rate-shaping may be an effective method of controlling the variable fuel flow from the injector and may allow the replacement of multi-stage fuel injection. Graphical Abstract

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Model-based within-a-cycle estimation of rate shaping for a piezoelectric fuel injector

Cited by 3 publications

References 14 publications

Model-based estimation of piezoelectric fuel injector parameters

Model-based estimation of piezoelectric fuel injector parameters

Low-order control-oriented modeling of piezoelectric actuator using Huberian function with low threshold: pseudolinear and neural network models

Fuel injection rate shaping and its effect on spray parameters in a direct-injection gasoline system

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