2DOF PID for dynamic control of drive system hybrid vehicle electrical

Hmidi, Mohamed Elhedi; Salem, Ines Ben; Amraoui, Lilia El

doi:10.1109/gecs.2017.8066178

Cited by 5 publications

(3 citation statements)

References 6 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…According to equations ( 5) and ( 7), the HVP target displacement can be calculated with equation (6) and is shown in equation (8).…”

Section: Multi-factor Pump Target Displacement Control Rules Based On...mentioning

confidence: 99%

“…For example, PID controllers with two degrees of freedom are used for speed control and stabilization of various vehicle structures. 8 Nonlinear PID with feedforward control is applied in smart car systems to improve the dynamic performance and stability of vehicles. 6 The PID + feedforward control strategy is utilized in the hydraulic active stabilizer bar systems to coordinate vehicle roll and yaw motions.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Model predictive control based on time-varying efficiency for hydraulic hub-motor driving vehicle

Song

2021

Proceedings of the Institution of Mechanical Engineers, Part D:

View full text Add to dashboard Cite

A model predictive feedback control strategy based on time-varying efficiency is investigated and applied to a hydraulic hub-motor auxiliary system (HHMAS) in this paper. Adding HHMAS to a traditional heavy commercial vehicle can improve fuel economy and traction performance on roads with low adhesion coefficients. However, the hydraulic drive system experiences serious disturbance imposed by time-varying parameters and external conditions. Model predictive feedback control based on time-varying efficiency offers a solution for HHMAS to cope with the disadvantage of the hydraulic drive system and improve the environmental adaptability of the vehicle controller. In this study, the control law of hydraulic variable pump (HVP) target displacement is established based on temperature compensation in consideration of the influence of multiple factors on pump target displacement. For coordinated power distribution of HHMAS, the minimum wheel speed difference and the reduction in system impact are regarded as optimal control targets in adjusting the engine torque and HVP displacement and designing the model predictive controller. Simulation results show that the proposed model predictive control method can reduce the speed difference between front and rear wheels by up to 64% and can achieve the wheel speed following effect faster than the traditional proportional-integral-derivative algorithm. Given that the control parameters do not need to be calibrated in the proposed method, the calibration time is saved, and the actual development process of the hydraulic hub-motor driving vehicle is remarkably improved.

show abstract

“…According to equations ( 5) and ( 7), the HVP target displacement can be calculated with equation (6) and is shown in equation (8).…”

Section: Multi-factor Pump Target Displacement Control Rules Based On...mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Model predictive control based on time-varying efficiency for hydraulic hub-motor driving vehicle

Song

2021

Proceedings of the Institution of Mechanical Engineers, Part D:

View full text Add to dashboard Cite

show abstract

“…Moreover, the PID controller is used for controlling the displacement of the vehicle. Mohamed Elhadi Hmidi et al [8] introduced a dynamic model and PID controller for controlling the displacement and acceleration of the vehicle. Wael Farag [9] proposed an approach for the detection and tracking of Street lanes.…”

Section: Introductionmentioning

confidence: 99%

An Economically Efficient Agent-based Autonomous Road Cleaner for Asian Cities

HAMZA

Riaz

Abid

et al. 2021

International Journal of Automotive Science and Technology

View full text Add to dashboard Cite

In the last couple of decades, autonomous road cleaners have been enormously attracting the world. For this purpose, numerous researchers have contributed to designing efficient, robust, and human-friendly cleaning mechanisms. However, their proposed approaches do not provide a cost-effective solution due to the deployment of exorbitant sensors and sophisticated infrastructure deployment. Hence, we propose to develop a cost-effective self-driving road that has the capability to clean the roads of major cities of Asia. The developed road cleaner efficiently detects road lanes using advanced machine vision techniques and estimates the angle to stay in the lane. Moreover, to control the speed of the road cleaner we have used a proportional–integral–derivative (PID) controller. The smart cleaning robot detects objects in its surroundings to prevent accidents in congested roads; thus it will have a function of anticollision and automatic avoidance. It also measures turning angle by performing computations on the position of road lanes and takes turns accordingly. To validate the efficiency of the proposed solution, we have performed a series of experiments considering different test cases.

show abstract