Antilock braking control using robust control approach

The aims of this study are to establish the mathematical model and the robust control technique for an Antilock Braking System (ABS). The ABS have been developed to reduce tendency of wheel lock up and to improve vehicle control during sudden braking. The ABS work by maintaining the wheel slip to a desired level so that maximum tractive force and maximum vehicle deceleration is obtained, thus reducing the vehicle stopping distance. A quarter vehicle model undergoing straightline braking maneuver, tire dynamics and hydraulic brake dynamics mathematical model are developed to represent the ABS model. The established mathematical model shows the ABS dynamics exhibits strong nonlinear characteristics. Thus, Sliding Mode Control which is a robust control technique is proposed in this study to regulate the wheel slip at the desired value depending on the road surface. The mathematical derivations proved the designed controller satisfy the stability requirement. Extensive simulation study is performed to verify the effectiveness of the designed controller and the result shows the designed controller able to maintain the wheel slip at the desired value and reducing the stopping distanc

Smart Traction Control Systems for Electric Vehicles Using Acoustic Road-type Estimation

The application of traction control systems (TCS) for electric vehicles (EV) has great potential due to easy implementation of torque control with direct-drive motors. However, the control system usually requires road-tire friction and slip-ratio values, which must be estimated. While it is not possible to obtain the first one directly, the estimation of latter value requires accurate measurements of chassis and wheel velocity. In addition, existing TCS structures are often designed without considering the robustness and energy efficiency of torque control. In this work, both problems are addressed with a smart TCS design having an integrated acoustic road-type estimation (ARTE) unit. This unit enables the road-type recognition and this information is used to retrieve the correct look-up table between friction coefficient and slip-ratio. The estimation of the friction coefficient helps the system to update the necessary input torque. The ARTE unit utilizes machine learning, mapping the acoustic feature inputs to road-type as output. In this study, three existing TCS for EVs are examined with and without the integrated ARTE unit. The results show significant performance improvement with ARTE, reducing the slip ratio by 75% while saving energy via reduction of applied torque and increasing the robustness of the TCS.Comment: Accepted to be published by IEEE Trans. on Intelligent Vehicles, 22 Jan 201

Performance of Anti-Lock Braking Systems Based on Adaptive and Intelligent Control Methodologies

Automobiles of today must constantly change their speeds in reaction to changing road and traffic circumstances as the pace and density of road traffic increases. In sophisticated automobiles, the Anti-lock Braking System (ABS) is a vehicle safety system that enhances the vehicle's stability and steering capabilities by varying the torque to maintain the slip ratio at a safe level. This paper analyzes the performance of classical control, model reference adaptive control (MRAC), and intelligent control for controlling the (ABS). The ABS controller's goal is to keep the wheel slip ratio, which includes nonlinearities, parametric uncertainties, and disturbances as close to an optimal slip value as possible. This will decrease the stopping distance and guarantee safe vehicle operation during braking. A Bang-bang controller, PID, PID based Model Reference Adaptive Control (PID-MRAD), Fuzzy Logic Control (FLC), and Adaptive Neuro-Fuzzy Inference System (ANFIS) controller are used to control the vehicle model. The car was tested on a dry asphalt and ice road with only straight-line braking. Based on slip ratio, vehicle speed, angular velocity, and stopping time, comparisons are performed between all control strategies. To analyze braking characteristics, the simulation changes the road surface condition, vehicle weight, and control methods. The simulation results revealed that our objectives were met. The simulation results clearly show that the ANFIS provides more flexibility and improves system-tracking precision in control action compared to the Bang-bang, PID, PID-MRAC, and FLC

Vision-based active safety system for automatic stopping

ntelligent systems designed to reduce highway fatalities have been widely applied in the automotive sector in the last decade. Of all users of transport systems, pedestrians are the most vulnerable in crashes as they are unprotected. This paper deals with an autonomous intelligent emergency system designed to avoid collisions with pedestrians. The system consists of a fuzzy controller based on the time-to-collision estimate – obtained via a vision-based system – and the wheel-locking probability – obtained via the vehicle’s CAN bus – that generates a safe braking action. The system has been tested in a real car – a convertible Citroën C3 Pluriel – equipped with an automated electro-hydraulic braking system capable of working in parallel with the vehicle’s original braking circuit. The system is used as a last resort in the case that an unexpected pedestrian is in the lane and all the warnings have failed to produce a response from the driver

MODELING AND SIMULATION OF PM MOTOR TESTING ENVIRONMENT TOWARDS EV APPLICATION CONSIDERING ROAD CONDITIONS

The electric vehicle (EV) performance testing is an indispensable aspect of the design study and marketing of electric vehicle. The development of a suitable electric motor testing environment for EVs is very significant. On the one hand, it provides a relatively realistic testing environment for the study of the key technologies of electric vehicles, and it also plays an essential role in finding a reasonable and reliable optimization scheme. On the other hand, it provides a reference to the evaluation criteria for the products on the market. This thesis is based on such requirements to model and simulate the PM motor testing environment towards EV applications considering road conditions. Firstly, the requirements of the electric motor drive as a propulsion system for EV applications are investigated by comparing to that of the traditional engine as a propulsion system. Then, as the studying objective of this work, the mathematical model of PMSM is discussed according to three different coordinate systems, and the control strategy for EV application is developed. In order to test the PM motor in the context of an EV, a specific target vehicle model is needed as the virtual load of the tested motor with the dyno system to emulate the real operating environment of the vehicle. A slippery road is one of the severe driving conditions for EVs and should be considered during the traction motor testing process. Fuzzy logic based wheel slip control is adopted in this thesis to evaluate the PM motor performance under slippery road conditions. Through the proposed testing environment, the PM motor can be tested in virtual vehicle driving conditions, which is significant for improving the PM motor design and control

Passenger car active braking system: Pressure control design and experimental results (part II)

This paper deals with the design of a brake caliper pressure controller for a conventional anti-lock braking system/electronic stability control system and the experimental validation of its tracking performances. The analysis of the hydraulic plant, carried out in part I of this two-part study, is here utilized to develop the control algorithm. The control strategy is based on a feed-forward and a proportional integral controller through pulse width modulation with a constant frequency and variable duty cycle. The feed-forward contribution requires modeling of the nonlinear openloop system behavior which has been experimentally identified and described through two-dimensional maps: the inputs are the duty cycle applied to the electrovalves and the pressure drop across their orifice, while the output is the pressure gradient in the brake caliper. These maps, obtained for inlet and outlet valves, are used to set the feed-forward term. Finally a proportional integral controller is designed to reject external disturbances and compensate for model uncertainties. A brake system test rig, described in part I, is used for building inverse maps and validating the proposed control logic. Different reference pressure profiles are used to experimentally verify the control tracking performances

Development of an Electronic Stability Control for Improved Vehicle Handling using Co-Simulation

The research project focuses on integrating the algorithms of recent automotive Electronic Stability Control (ESC) technologies into a commercial multi-body dynamics (MBD) software for full vehicle simulations. Among various control strategies for ESC, the sliding mode control (SMC) method is proposed to develop these algorithms, as it is proven to be excellent at overcoming the effect of uncertainties and disturbances. The ESC model integrates active front steering (AFS) system and direct yaw moment control (DYC) system, using differential braking system, therefore the type of the ESC model is called as integrated vehicle dynamic control (IVDC) system. The IVDC virtual model will be designed using a specialized control system software, called Simulink. The controller model will be used to perform full vehicle simulations, such as sine with dwell (SwD) and double lane change (DLC) tests on Simulink to observe its functionality in stabilizing vehicles. The virtual nonlinear full vehicle model in CarSim will be equipped with the IVDC virtual model to ensure that the proposed IVDC virtual model passes the regulations that describes the ESC homologation process for North America and European countries, each defined by National Highway Traffic Safety Administration (NHTSA) and United Nations (UN). The proposed research project will enable automotive engineers and researchers to perform full vehicle virtual simulations with ESC capabilities

Model-based powertrain design and control system development for the ideal all-wheel drive electric vehicle

The transfer case based all-wheel drive electric vehicle (TCAWDEV) and dual-axle AWDEV have been investigated to balance concerns about energy consumption, drivability and stability of vehicles. However, the mentioned powertrain architectures have the torque windup issue or the wheel skidding issue. The torque windup is an inherent issue of mechanical linked all-wheel drive systems. The hydraulic motor-based or the electric motor-based ideal all-wheel drive powertrain can provide feasible solutions to the mentioned issues. An ideal AWDEV (IAWDEV) powertrain architecture and its control schemes were proposed by this research; the architecture has four independent driving motors in powertrain. The IAWDEV gives more control freedoms to implement active torque controls and traction mode controls. In essence, this research came up with the distributed powertrain concept, and developed control schemes of the distributed powertrain to replace the transfer case and differential devices. The study investigated the dual-loop motor control, the hybrid sliding mode control (HSMC) and the neural network predictive control to reduce energy consumption and achieve better drivability and stability by optimizing the torque allocation of each dependent wheel. The mentioned control schemes were respectively developed for the anti-slip, differential and yaw stability functionalities of the IAWDEV powertrain. This study also investigated the sizing method that the battery capacity was estimated by using cruise performance at 3% road grade. In addition, the model-based verification was employed to evaluate the proposed powertrain design and control schemes. The verification shows that the design and controls can fulfill drivability requirements and minimize the existing issues, including torque windup and chattering of the slipping wheel. In addition, the verification shows that the IAWDEV can harvest around two times more energy while the vehicle is running on slippery roads than the TCAWDEV and the dual-axle AWDEV; the traction control can achieve better drivability and lower energy consumption than mentioned powertrains; the mode control can reduce 3% of battery charge depleting during the highway driving test. It also provides compelling evidences that the functionalities achieved by complicated and costly mechanical devices can be carried out by control schemes of the IAWDEV; the active torque controls can solve the inherent issues of mechanical linked powertrains; the sizing method is credible to estimate the operation envelop of powertrain components, even though there is some controllable over-sizing