Computationally efficient filtering algorithms for engine torque estimation

A new computationally efficient filtering algorithm for the reconstruction of the first harmonic of a periodic signal is presented. The algorithm allows the recovery of the combustion quality information from the engine speed measurements that are noise contaminated. The algorithm is verified by using a spark ignition V8 engine in the torque estimation problem.

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Data-driven algorithms for engine friction estimation

Proceedings of the Institution of Mechanical Engineers Part D Journal of Automobile Engineering ◽

10.1243/09544070jauto230 ◽

2007 ◽

Vol 221 (7) ◽

pp. 901-909 ◽

Cited By ~ 9

Author(s):

A A Stotsky

Keyword(s):

Engine Speed ◽

Control Unit ◽

Spark Ignition ◽

Friction Torque ◽

Data Driven ◽

Periodic Signal ◽

Computationally Efficient ◽

Engine Torque ◽

Look Up Table ◽

Engine Friction

Errors in the estimation of friction torque in modern spark ignition automotive engines necessitate the development of real-time algorithms for adaptation of the friction torque. Friction torque in the engine control unit is presented as a look-up table with two input variables (the engine speed and indicated engine torque). The algorithms proposed in this paper estimate the engine friction torque via the crankshaft speed fluctuations at the fuel cut-off state and at idle. A computationally efficient filtering algorithm for reconstruction of the first harmonic of a periodic signal is used to recover an amplitude which corresponds to engine events from the noise-contaminated engine speed measurements at the fuel cut-off state. The values of the friction torque at the nodes of the look-up table are updated, when new measured data of the friction torque are available. New data-driven algorithms which are based on a stepwise regression method are developed for adaptation of look-up tables. The algorithms are verified by using a spark ignition six-cylinder prototype engine.

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Computationally efficient filtering algorithms for engine torque estimation

Proceedings of the 2005, American Control Conference, 2005. ◽

10.1109/acc.2005.1470809 ◽

2005 ◽

Cited By ~ 1

Author(s):

A. Stotsky ◽

I. Kolmanovsky

Keyword(s):

Computationally Efficient ◽

Filtering Algorithms ◽

Engine Torque ◽

Torque Estimation

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A Control-Oriented Engine Torque Online Estimation Approach for Gasoline Engines Based on In-Cycle Crankshaft Speed Dynamics

Energies ◽

10.3390/en12244683 ◽

2019 ◽

Vol 12 (24) ◽

pp. 4683

Author(s):

Qiang Tong ◽

Hui Xie ◽

Kang Song ◽

Dong Zou

Keyword(s):

Real Time ◽

Engine Speed ◽

Estimation Error ◽

Control Unit ◽

Friction Torque ◽

Adaptive Observer ◽

Load Torque ◽

Engine Torque ◽

Brake Torque ◽

Torque Estimation

Engine brake torque is a key feedback variable for the optimal torque split control of an engine–motor hybrid powertrain system. Due to the limitations in available sensors, however, engine torque is difficult to measure directly. For torque estimation, the unknown external load torque and the overlap of the expansion stroke between cylinders introduce a great disturbance to engine speed dynamics. This makes the conventional cycle average engine speed-based estimation approach unusable. In this article, an in-cycle crankshaft speed-based indicated torque estimation approach is proposed for a four-cylinder engine. First, a unique crankshaft angle window is selected for load torque estimation without the influence of combustion torque. Then, an in-cycle angle-domain crankshaft speed dynamic model is developed for engine indicated torque estimation. To account for the effects of model inaccuracy and unknown external disturbances, a “total disturbance” term is introduced. The total disturbance is then estimated by an adaptive observer using the engine’s historical operating data. Finally, a real-time correction method for the friction torque is proposed in the fuel cut-off scenario. Combining the aforementioned torque estimators, the brake torque can be obtained. The proposed algorithm is implemented in an in-house developed multi-core engine control unit (ECU). Experimental validation results on an engine test bench show that the algorithm’s execution time is about 3.2 ms, and the estimation error of the brake torque is within 5%. Therefore, the proposed method is a promising way to accurately estimate engine torque in real-time.

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Real-Time Estimation of Engine Torque Using Speed Wheel Information

Dynamic Systems and Control, Parts A and B ◽

10.1115/imece2006-13334 ◽

2006 ◽

Author(s):

J. Franco ◽

M. A. Franchek ◽

K. M. Grigoriadis

Keyword(s):

Steady State ◽

Real Time ◽

Engine Speed ◽

Notch Filter ◽

Time Estimation ◽

Estimation Algorithm ◽

Frequency Component ◽

Engine Torque ◽

Torque Estimation ◽

Crank Angle

Presented is a real-time steady state engine torque estimation algorithm executed in the spatial domain (crank angle domain) using speed wheel information. The torque estimation algorithm consists of a notch-filter and a steady state model which is identified using an orthogonal least squares estimation algorithm. The inputs to this model include the amplitude of the nth frequency component (n is the number of cylinders) of the crankshaft signature and average engine speed. Notch filters executed in the crank-angle domain are employed to extract the nth frequency component directly from the instantaneous engine speed signal. This approach is applied to a calibrated engine model for an in-line six cylinder diesel engine. A discussion of the results is also provided.

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Measurement of Impact of Air Filter Cleanness on a Change of Engine Speed Characteristics

Transport and Communications ◽

10.26552/tac.c.2017.1.5 ◽

2017 ◽

Vol 5 (1) ◽

pp. 21-23

Author(s):

František Synák ◽

◽

Vladimír Rievaj

Keyword(s):

Engine Speed ◽

Spark Ignition ◽

Spark Ignition Engine ◽

Air Filter ◽

Engine Torque ◽

The Impact

The paper is focused on the impact of clogged air filter on a change of speed characteristics of spark-ignition engine 1.4 MPI, 16V, 74 kW. The clogged air filter can cause deterioration in engine charging. Less air means the possibility of burning smaller amount of fuel, and thus less energy brought to the engine. This should cause a change in the size of engine torque and its power.

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