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

Energies ◽  
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.

Data-driven algorithms for engine friction estimation

2007 ◽  
Vol 221 (7) ◽  
pp. 901-909 ◽  
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.

Real-Time Estimation of Engine Torque Using Speed Wheel Information

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.

Real-time brake torque estimation for internal combustion engines

2008 ◽  
Vol 22 (2) ◽  
pp. 338-361 ◽  
Author(s):  
Javier Franco ◽  
Matthew A. Franchek ◽  
Karolos Grigoriadis
Keyword(s):  
Real Time ◽  
Internal Combustion Engines ◽  
Internal Combustion ◽  
Combustion Engines ◽  
Brake Torque ◽  
Torque Estimation

Torque estimation of spark ignition engines via cylinder pressure measurement

2003 ◽  
Vol 217 (9) ◽  
pp. 809-817 ◽  
Author(s):  
Seungbum Park ◽  
Myoungho Sunwoo
Keyword(s):  
Engine Management System ◽  
Engine Control ◽  
Spark Ignition Engines ◽  
Cylinder Pressure ◽  
Load Torque ◽  
Engine Torque ◽  
Estimation Algorithms ◽  
Torque Estimation ◽  
Feasible Alternative ◽  
Vehicle Dynamics Control

Indicated torque estimation and load torque observation algorithms are presented and appear to be a feasible alternative to the use of the engine torque maps in a modern torque-based engine management system. The proposed method, which uses a cylinder pressure sensor, has advantages of simplicity from the elimination of the requirement for a complex indicated torque model. Moreover, the proposed algorithms are accurate and robust to the variations in the environmental factors that affect the torque production procedure. The indicated torque is estimated from the peak pressure and its location, and the load torque is observed on the basis of the estimated indicated torque. The proposed torque estimation algorithms may provide new ideas for many application areas such as engine diagnostics, torque-based engine control, traction control via engine control, and vehicle dynamics control.

scholarly journals Computationally efficient filtering algorithms for engine torque estimation

2005 ◽  
Vol 219 (9) ◽  
pp. 1099-1107 ◽  
Author(s):  
A Stotsky
Keyword(s):  
Engine Speed ◽  
Spark Ignition ◽  
Estimation Problem ◽  
Quality Information ◽  
Periodic Signal ◽  
Computationally Efficient ◽  
Filtering Algorithms ◽  
Engine Torque ◽  
Filtering Algorithm ◽  
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.

Traction control using a throttle valve based on sliding mode control and load torque estimation

2005 ◽  
Vol 219 (5) ◽  
pp. 645-653 ◽  
Author(s):  
Sangmin Kang ◽  
Maru Yoon ◽  
Myoungho Sunwoo
Keyword(s):  
Sliding Mode Control ◽  
Controller Design ◽  
Sliding Mode ◽  
Load Torque ◽  
Traction Control ◽  
Engine Torque ◽  
Engine Model ◽  
Mode Control ◽  
Throttle Valve ◽  
Torque Estimation

The purpose of an engine-controlled traction control system (TCS) is to regulate engine torque in order to keep the driven wheel slip in a desired range. Engine torque can be regulated by a throttle valve. In this paper, the engine-controlled TCS based on an engine model and estimated load torque by a Luenberger observer is proposed. For this control scheme, the engine model is required for a model-based controller design using sliding mode control. The engine torque controller determines the throttle angle for maintaining the desired manifold pressure to generate engine torque corresponding to the desired wheel torque. Since the load torque is composed of multiple external sources such as friction force, drag force, mechanical losses, and others, load torque estimation is required. The simulation results to various manoeuvres during slippery and split road conditions have showed better acceleration performance and stability of the vehicle with TCS. In addition, the load torque observer has estimated real load torque with little error.

Network Selection in Wireless Heterogeneous Environment Based on Available Bandwidth Estimation

2019 ◽  
Vol 12 ◽  
Author(s):  
Kiran Ahuja ◽  
Brahmjit Singh ◽  
Rajesh Khanna
Keyword(s):  
Real Time ◽  
Estimation Error ◽  
Network Selection ◽  
Bandwidth Estimation ◽  
Heterogeneous Environment ◽  
Bootstrap Approximation ◽  
Available Bandwidth ◽  
Internet Connection ◽  
Available Bandwidth Estimation ◽  
Selection Of

Background: With the availability of multiple options in wireless network simultaneously, Always Best Connected (ABC) requires dynamic selection of the best network and access technologies. Objective: In this paper, a novel dynamic access network selection algorithm based on the real time is proposed. The available bandwidth (ABW) of each network is required to be estimated to solve the network selection problem. Method: Proposed algorithm estimates available bandwidth by taking averages, peaks, low points and bootstrap approximation for network selection. It monitors real-time internet connection and resolves the selection issue in internet connection. The proposed algorithm is capable of adapting to prevailing network conditions in heterogeneous environment of 2G, 3G and WLAN networks without user intervention. It is implemented in temporal and spatial domains to check its robustness. Estimation error, overhead, estimation time with the varying size of traffic and reliability are used as the performance metrics. Results: Through numerical results, it is shown that the proposed algorithm’s ABW estimation based on bootstrap approximation gives improved performance in terms of estimation error (less than 20%), overhead (varies from 0.03% to 83%) and reliability (approx. 99%) with respect to existing techniques. Conclusion: Our proposed methodology of network selection criterion estimates the available bandwidth by taking averages, peaks, and low points and bootstrap approximation method (standard deviation) for the selection of network in the wireless heterogeneous environment. It monitors real-time internet connection and resolves internet connections selection issue. All the real-time usage and test results demonstrate the productivity and adequacy of available bandwidth estimation with bootstrap approximation as a practical solution for consistent correspondence among heterogeneous wireless networks by precise network selection for multimedia services.

scholarly journals Performance Analysis of a Full Order Sensorless Control Adaptive Observer for Doubly-Fed Induction Generator in Grid Connected Operation

Energies ◽  
2021 ◽  
Vol 14 (5) ◽  
pp. 1254
Author(s):  
Gianluca Brando ◽  
Adolfo Dannier ◽  
Ivan Spina
Keyword(s):  
Sensorless Control ◽  
Estimation Error ◽  
Position Estimation ◽  
Adaptive Observer ◽  
Induction Generator ◽  
Doubly Fed Induction Generator ◽  
Rotor Position ◽  
Stator Flux ◽  
Doubly Fed ◽  
Rotor Position Estimation

This paper focuses on the performance analysis of a sensorless control for a Doubly Fed Induction Generator (DFIG) in grid-connected operation for turbine-based wind generation systems. With reference to a conventional stator flux based Field Oriented Control (FOC), a full-order adaptive observer is implemented and a criterion to calculate the observer gain matrix is provided. The observer provides the estimated stator flux and an estimation of the rotor position is also obtained through the measurements of stator and rotor phase currents. Due to parameter inaccuracy, the rotor position estimation is affected by an error. As a novelty of the discussed approach, the rotor position estimation error is considered as an additional machine parameter, and an error tracking procedure is envisioned in order to track the DFIG rotor position with better accuracy. In particular, an adaptive law based on the Lyapunov theory is implemented for the tracking of the rotor position estimation error, and a current injection strategy is developed in order to ensure the necessary tracking sensitivity around zero rotor voltages. The roughly evaluated rotor position can be corrected by means of the tracked rotor position estimation error, so that the corrected rotor position is sent to the FOC for the necessary rotating coordinate transformation. An extensive experimental analysis is carried out on an 11 kW, 4 poles, 400 V/50 Hz induction machine testifying the quality of the sensorless control.

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