Adaptive Estimation of the Engine Friction Torque

Stotsky, Alexander

doi:10.1109/cdc.2005.1583240

Cited by 3 publications

(2 citation statements)

References 4 publications

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“…where, Q L is the load flow (m 3 /s); K q is the flow gain (m 2 /s); X v is the spool displacement (m); K c is the flow pressure coefficient (m 3 /(s•Pa)); and P L is the external load pressure (MPa). However, most classical friction models are derived from the static mapping relationship between relative velocity and friction with a symbolic function assigning the direction of the friction force, and this discontinuous or segmented continuous friction model can cause system instability [16][17][18]. For the slide-mode variable structure controller, the system state is continuously reciprocating along the slide-mode surface due to the switching function, resulting in the "chattering" phenomenon [19,20].…”

Section: Continuous Rotary Motor State Space Modelingmentioning

confidence: 99%

Friction Feedforward Compensation Composite Control of Continuous Rotary Motor with Sliding Mode Variable Structure Based on an Improved Power Reaching Law

2023

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In order to meet the accuracy requirements and tracking performance of continuous rotary electro-hydraulic servo motor system under nonlinear uncertainty and strong disturbance factors, the sliding mode variable structure composite control strategy based on an improved power reaching law is proposed. Based on the principle of valve-controlled hydraulic motor, the state space model of the motor system is established, and a continuous friction model is adopted. Then, the genetic algorithm is used for parameter identification to determine the friction feedforward compensation scheme. In addition, an improved power reaching law is designed, which can adaptively adjust the system chattering according to the system state. The simulation results show that the sliding mode variable structure composite controller with the friction feedforward compensation can achieve a system frequency of 15 Hz, and tracking accuracy and response speed meet the double-decade index requirements, which improve the performance of continuous rotary electro-hydraulic servo motor.

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Section: Continuous Rotary Motor State Space Modelingmentioning

confidence: 99%

Friction Feedforward Compensation Composite Control of Continuous Rotary Motor with Sliding Mode Variable Structure Based on an Improved Power Reaching Law

2023

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“…The clutch torque is also used for driveline control applications [6] [7]. The mapping of the engine torque linked to several inputs like the engine speed, the throttle position, the cylinder pressure and the temperature [8] [9][10] [11] is commonly used in the automotive industry. But these engine torque maps are obtained from several trials done on test benches on a unique engine which are generalized to a set of engines regardless the dispersion.…”

Section: Introductionmentioning

confidence: 99%

Discrete angular torque observer applicated to the engine torque and clutch torque estimation via a dual-mass flywheel

Losero¹,

Lauber²,

Guerra³

2015

2015 IEEE 10th Conference on Industrial Electronics and Applications (ICIEA)

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The interest in engine torque and clutch torque estimation is important in the automotive industry. They are determinant variables in engine and powertrain management like hybrid engine vehicle, automated transmission and energy saving strategies. An instantaneous brake engine torque and transmitted clutch torque estimation method based on discrete angular domain fuzzy observer using a torsion angle calculation is proposed in this paper. It is applied on a filtration device; the dual mass flywheel. The observer permits to obtain good experimental results of the engine torque and clutch torque estimation.

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A Moment-of-Inertia-Driven Engine Start-Up Method Based on Adaptive Model Predictive Control for Hybrid Electric Vehicles With Drivability Optimization

Jian-bo

Hou

et al. 2020

IEEE Access

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During the deceleration phase of a hybrid electric vehicle (HEV), a moment-of-inertia-driven (MoI-driven) engine start-up process can provide a potential economic benefit because it reduces the energy consumption of the starting device. During this start-up process, it is important to maintain drivability by enabling a quick start-up, low driveline vibration, and fast response to torque demand. The wheel rolling distance control should also be considered. This paper proposes electrical motor (EM) participation in an MoI-driven engine start-up process and studies an adaptive model-based predictive optimization method for the drivability control of P2 parallel hybrid vehicles. Based on a new triple mass-spring-system model, an adaptive model predictive controller (MPC) is designed with EM torque set points, clutch friction torque set points, and engine torque set points as manipulated inputs and engine speed, torsion speed, and wheel rolling distance as the measured outputs. A predicted torque demand is introduced to enhance the torque response performance. By considering the constraints of power source components, an optimization algorithm is developed. A simulation is conducted to verify the control strategy on the HEV powertrain and on vehicle dynamics models. The results show that under the same level of start-up, the torsion speed can be reduced by up to 50% with an improved wheel rolling distance and low torque demand error during a certain deceleration.

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Adaptive Estimation of the Engine Friction Torque

Cited by 3 publications

References 4 publications

Friction Feedforward Compensation Composite Control of Continuous Rotary Motor with Sliding Mode Variable Structure Based on an Improved Power Reaching Law

Friction Feedforward Compensation Composite Control of Continuous Rotary Motor with Sliding Mode Variable Structure Based on an Improved Power Reaching Law

Discrete angular torque observer applicated to the engine torque and clutch torque estimation via a dual-mass flywheel

A Moment-of-Inertia-Driven Engine Start-Up Method Based on Adaptive Model Predictive Control for Hybrid Electric Vehicles With Drivability Optimization

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