Optimal vehicle dynamics controller design using a four-degrees-of-freedom model

Mashadi, Behrooz; Majidi, Majid; Dizaji, H Pourabdollah

doi:10.1243/09544070jauto1280

Cited by 13 publications

(9 citation statements)

References 16 publications

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“…Considering the longitudinal speed, lateral speed, roll angle, and height of the centroid of the forklift, the vertical load of each tire of the forklift can also be generated. The variation, through the kinetic analysis, can be calculated as follows : Left steering wheel (left rear wheel) vertical load:

F_{italiczlf} = \frac{m}{L} (\frac{italicgb}{2} - \frac{H \dot{u}}{2} - \frac{bH ({\overset{v}{true}}_{y} + u ω_{r})}{d_{r}}) + \frac{m_{s} {italicgbh}_{s}}{d_{r} L} \sin ϕ

…”

Section: Tfc35 Forklift Dynamic Modelsmentioning

confidence: 99%

Research on active steering control strategy based on sideslip angle estimation for a steering‐by‐wire forklift

Zhang

Xiao

2019

IEEJ Transactions Elec Engng

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Taking the TFC35 electric forklift as the research object, we analyze the movements and forces of the forklift in three directions: yaw, lateral movement, and roll. Combined with the load transfer formula of the forklift and the nonlinear and linear tire model, the formula for lateral force of the four tires of forklift is deduced, and the nonlinear and linear three-degree-of-freedom (3DOF) forklift dynamics model is established. Because the sideslip angle of the forklift is not easy to measure directly, based on the linear 3DOF forklift model, we take the yaw rate and lateral angle as the observation variables and consider the influence of model error. An adaptive Kalman filter is designed to estimate the sideslip angle of the forklift. In order to improve the accuracy of estimation, an online optimization strategy of the adaptive Kalman filter based on genetic algorithm with an adaptive factor is proposed. Simulation results show the effectiveness of the proposed method. In combination with the forklift reference model, the rear wheel angle of the forklift is corrected by comprehensive proportional feedback of yaw rate and the sideslip angle, and the active steering system for a steering-by-wire forklift is designed. Simulation and test results show that the control strategy of forklift's active steering system can improve its driving stability and handling performance.RESEARCH ON ACTIVE STEERING CONTROL STRATEGY state, we use two proportional controllers to realize the controller design of the forklift's active steering system. The steering angle of the controller can be integrated into the feedback correction of forklift truck according to the traveling state in real time. We provide simulation and experimental verification. TFC35 Forklift Dynamic ModelsThe TFC35 electric forklift uses a rear-wheel-drive, rear-wheelsteering design. The parameters of the TFC35 forklift dynamic model are as follows: weight = 8720 kg, rated load = 4000 kg, vehicle length = 2300 mm, width = 2855 mm, maximum speed = 12 km/h, maximum steering wheel angle = ±90 • .

show abstract

F_{italiczlf} = \frac{m}{L} (\frac{italicgb}{2} - \frac{H \dot{u}}{2} - \frac{bH ({\overset{v}{true}}_{y} + u ω_{r})}{d_{r}}) + \frac{m_{s} {italicgbh}_{s}}{d_{r} L} \sin ϕ

…”

Section: Tfc35 Forklift Dynamic Modelsmentioning

confidence: 99%

Research on active steering control strategy based on sideslip angle estimation for a steering‐by‐wire forklift

Zhang

Xiao

2019

IEEJ Transactions Elec Engng

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“…For simulation and control design was used a model that considers lateral, yaw and roll motions with simplifications for constant longitudinal speed [2,12,15,25]. Figure 1 shows this model represented by the following equations of motions:…”

Section: Vehicle Dynamicmentioning

confidence: 99%

Development and evaluation with MIL and HIL simulations of a LQR-based upper-level electronic stability control

Magalhães

Murilo

Lopes

2019

J Braz. Soc. Mech. Sci. Eng.

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This paper proposes an electronic stability control and shows MIL and HIL simulations performed for evaluation. Two designs are presented, one based on two-degrees-of-freedom linear model that includes side-slip and yaw motion and other based on three-degrees-of-freedom linear model that includes roll motion. Model-in-the-loop and Hardware-in-the-loop simulations were performed to test ESC on vehicle represented by a nonlinear model that considers lateral, yaw and roll motions and an intelligent driver model to generate the steering wheel command as driver reaction to vehicle motion in respect with desired path. It's found from simulations for double lane change maneuver that the proposed controller is effective in reducing of sideslipping, rolling and yaw rate errors, keeping the steering stable in scenarios where the driver loses control of the vehicle, even in presence of disturbances in vehicle response in relation with response predicted by linear model used for control design. Keywords Electronic stability control • Linear quadratic regulator • Hardware-in-the-loop • Vehicle steering dynamic List of symbols a Length from front axis to center of mass b Length from rear axis to center of mass l Vehicle total length from rear axis to front axis t f Front track width t r Rear track width h s Height of center of mass above rolling center h Height of center of mass m s Sprung mass I zz Yawing inertial moment I xx Rolling inertial moment I xz Inertial product related to yawing and rolling c f Front rolling damping coefficient c r Rear rolling damping coefficient k f Front rolling stiffness coefficient k r Rear rolling stiffness coefficient f ∕ Front steer-by-roll coefficient M u Extra yaw moment given as control signal I s Steering coefficient u Vehicle longitudinal speed v Vehicle lateral speed Yaw angle Roll angle f Steering angle of front wheels r Steering angle of rear wheels D Front steer angle due to the driver's steering wheel command F yi Lateral force generated by tire i Camber angle i Tire slip angle of wheel i Vehicle side-slip angle g Gravity acceleration C i Cornering stiffness of wheel i C i Camber stiffness K Camber gradient r ∕ Rear steer-by-roll coefficient Tire-road friction coefficient

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“…The degrees of freedom are the vehicle lateral speed and yaw rate. The governing equations of the 2-DOF model can be described as follows 22…”

Section: Vehicle-dynamics Modellingmentioning

confidence: 99%

Two-phase optimal path planning of autonomous ground vehicles using pseudo-spectral method

Mashadi

Majidi

2014

Proceedings of the Institution of Mechanical Engineers, Part K:

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In this paper, an optimal path-planning method is proposed for autonomous ground vehicles in case of overtaking a moving obstacle by the application of a two-phase optimal-control problem. When the autonomous vehicle detects a moving vehicle in a proper speed and distance ahead, it decides to overtake the obstacle by executing a double-lane change manoeuvre. The path for the overtaking manoeuvre is generated by a two-phase optimal path-planning problem. The cost function of the first phase is defined in such a way that the vehicle approaches the obstacle as close as possible.In the second phase, the cost function is defined as sum of the vehicle lateral deviation from the reference path and the rate of steering angle. At the same time, the lateral acceleration of the vehicle must not exceed a specified limit. The radio pseudo-spectral method, which is a method for direct trajectory optimization using global collocation at Legendre-Gauss-Radau points, is applied for solving the two-phase nonlinear optimal-control problem. A full nonlinear vehicle model in CarSim software is used for path-tracking simulation by importing path data from a MATLAB code. The simulation results show that the generated path for the autonomous vehicle satisfies all vehicle-dynamics constraints and hence is applicable for a real autonomous vehicle.

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Optimal vehicle dynamics controller design using a four-degrees-of-freedom model

Cited by 13 publications

References 16 publications

Research on active steering control strategy based on sideslip angle estimation for a steering‐by‐wire forklift

Research on active steering control strategy based on sideslip angle estimation for a steering‐by‐wire forklift

Development and evaluation with MIL and HIL simulations of a LQR-based upper-level electronic stability control

Two-phase optimal path planning of autonomous ground vehicles using pseudo-spectral method

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