Design of a Fuzzy Controller for Independent Control of Front Wheels Steering Angles

In this paper, a comparison is made on different torque vectoring strategies to find the best strategy in terms of improving handling, fuel consumption, stability and ride comfort performances. The torque vectoring differential strategies include superposition clutch, stationary clutch, four-wheel drive and electronic stability control. The torque vectoring differentials are implemented on an eight-DOF vehicle model and controlled using optimized fuzzy-based controllers. The vehicle model assisted with the Pacejka tyre model, an eight-cylinder dynamic model for engine, and a five-speed transmission system. Bee's Algorithm is employed to optimize the fuzzy controller to ensure each torque vectoring differential works in its best state. The controller actuates the electronic clutches of the torque vectoring differential to minimize the yaw rate error and limiting the side-slip angle in stability region. To estimate side-slip angle and cornering stiffness, a combined observer is designed based on full order observer and recursive least square method. To validate the results, a realistic car model is built in Carsim package. The final model is tested using a co-simulation between Matlab and Carsim. According to the results, the torque vectoring differential shows better handling compared to electronic stability control, while electronic stability control is more effective in improving the stability in critical situation. Among the torque vectoring differential strategies, stationary clutch in handling and four-wheel drive in fuel consumption as well as ride comfort have better operation and more enhancements.

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“…In equation (6), T e is the output torque, ! e is the engine speed and thr is different percentage of throttle position.…”

Section: The Tyre and Engine Modelsmentioning

confidence: 99%

“…Besides the decrease of the longitudinal performances, ESC increases fuel consumption. 2,3,6 Asymmetric distribution of traction force using torque vectoring differentials could be a solution. These systems are able to actively transfer appropriate controlled torque to each wheel, without braking.…”

Section: Introductionmentioning

confidence: 99%

A comparison on optimal torque vectoring strategies in overall performance enhancement of a passenger car

Jaafari

Shirazi

2016

Proceedings of the Institution of Mechanical Engineers, Part K:

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“…In order to illustrate the advantages of the presented controller, the results of the robust LQR controller are compared with the corresponding results of the classical LQR controller which is designed for the nominal vehicle parameters. The weight matrices which are used in controller design are Q = diag(100, 500, 500) R = diag (10,10) ð39Þ…”

Section: Robust Lqr Controller Performancementioning

confidence: 99%

“…The steering assistance system aims to avoid unintended lane departure during normal driving; in that work a linear state feedback controller was used for this purpose, based on a bicycle vehicle model. Moreover, Goodarzi et al 10 used fuzzy controllers to design an active steering system. Also, the independence of the front wheels was considered in their study.…”

Section: Introductionmentioning

confidence: 99%

Active front-steering control of a sport utility vehicle using a robust linear quadratic regulator method, with emphasis on the roll dynamics

Elmi

Ohadi

Samadi

2013

Proceedings of the Institution of Mechanical Engineers, Part D:

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One of the well-known methods for improving the lateral stability of a vehicle is to utilize an active steering controller. Common active steering systems use feedback signals from a yaw rate sensor and side-slip angle estimation. However, in some driving conditions, skilled drivers can prevent vehicle rollover using the steering angle of the vehicle. Hence, the effect of an active front-steering controller on the roll angle of the vehicle is studied in this paper. For this study, a three-degree-of-freedom linear model of a vehicle which has the lateral motion, the yaw motion and the roll motion as the degrees of freedom is derived. The effectiveness of the active steering controller on the roll stability of the vehicle is examined by simulations in a wide range of longitudinal velocities of the vehicle using a linear quadratic regulator controller. The results obtained indicate that the active steering controller increases the roll stability of the vehicle only at low vehicle speeds and also that consideration of the roll degree of freedom in the design of the active steering controller is not effective at high vehicle speeds. Therefore a two-degree-of-freedom bicycle model is sufficient for active steering controller design. Another part of this paper is dedicated to designing a practical active steering controller for a vehicle with time-varying and uncertain parameters. In fact, designing a controller which guarantees the stability of the vehicle with simultaneous uncertainties in the cornering stiffnesses of the tyres and in the time-varying velocity is the main goal of this paper. Another important advantage of the proposed controller is its simplicity and static structure. In fact, this controller design is carried out offline and can be implemented for use in a real vehicle. This simple and powerful controller is a robust linear quadratic regulator controller. For designing a robust linear quadratic regulator controller, a polytopic model of the two-degree-of-freedom vehicle is obtained, which considers the uncertainty in the parameters. In addition, a linear matrix inequality is used to design a linear quadratic regulator controller for an uncertain or parameter-varying system. Finally, the performance of the designed robust linear quadratic regulator controller was studied by simulating the vehicle responses in some manoeuvres. A sport utility vehicle model is used for simulation purposes. This non-linear vehicle model has eight degrees of freedom and its tyres are assumed to be both linear and non-linear. The performance of the robust linear quadratic regulator controller was studied for vehicles with both linear and non-linear Pacejka tyres. The proposed controller guarantees robust stability of the closed-loop system in the presence of 50% variation in the vehicle speed and 20% uncertainty in the stiffnesses of the tyres.

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Handling safety improvement for steer-by-wire vehicle using fuzzy controller

Elmi

Samadi

Ohadi

2011

The 2nd International Conference on Control, Instrumentation and Automation

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Design of a Fuzzy Controller for Independent Control of Front Wheels Steering Angles

Cited by 3 publications

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A comparison on optimal torque vectoring strategies in overall performance enhancement of a passenger car

A comparison on optimal torque vectoring strategies in overall performance enhancement of a passenger car

Active front-steering control of a sport utility vehicle using a robust linear quadratic regulator method, with emphasis on the roll dynamics

Handling safety improvement for steer-by-wire vehicle using fuzzy controller

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