Electronic Stability Control System Research Articles

Collaborative control of path tracking and roll stability in intelligent commercial vehicle: A minimax robust regulator based on Nash game

—Currently, most vehicles are generally equipped with roll stability control system or electronic stability control system to improve stability. However, when encountering emergency obstacle avoidance and similar conditions, roll stability control system may compete with path tracking control system for vehicle control, resulting in the inability to balance path tracking and roll stability. Therefore, a closed-loop feedback Nash game collaborative control method is proposed to solve the collaborative problem between the two control systems. Firstly, a fifth-order vehicle model with coupled yaw-roll dynamics is presented, which was extended to a vehicle-road closed-loop model based on lateral position, yaw angle and road preview information. Secondly, the path tracking control system and roll stability control system are regarded as two agents in the dynamic game control process. On this basis, a Nash game collaborative control strategy is designed by fully considering the control interaction between two game agents. Finally, considering the influence of uncertain disturbances, a finite-time minimax robust control strategy is proposed by using minimax optimization theory. Simulation and hardware in loop experiments show that the minimax robust regulator based on Nash game controller can effectively improve the path tracking and roll stability performance of vehicles. Moreover, the regulator improves the robustness of the system when it is subjected to bounded uncertain lateral disturbances.

Increasing the Safety of the Car

Road safety has improved significantly in recent years thanks to effective action taken at European and national level with changes in legislation related to improving driver and road training. As a result, EU roads are some of the safest in the world. The EU has introduced mandatory fitment of electronic stability control systems on all vehicles and advanced emergency braking and lane departure warning systems, contributing to a reduction in fatalities. Modern active safety technologies are increasingly being implemented in vehicles. The purpose of this report is to present a complex of systems, their functionality, benefit and significance for increasing road safety.

Analytical review of electronic and electrome-chanical systems of electric vehicles

Problem. This article addresses the issue of developing environmentally friendly vehicles and their electronic and electromechanical components. It provides an analytical review of advanced electromechanical technologies utilized in the creation of Tesla electric cars. Specifically, the study analyzes the electronic stability control system, active pneumatic suspension, and electric power steering. The perspective of electric cars lies in their ability to meet the economic requirements of modernity and align with the "Zero Emission" paradigm. The obtained results can serve as recommendations for the development of electronic and electromechanical systems and complexes of electric vehicles, benefiting scientific and technical professionals engaged in the creation of environmentally friendly vehicles. Goal. This study aims to analyze the advanced technologies used in the development of electronic and electromechanical systems of Tesla electric cars. Methodology. The research employs an analytical study of the characteristics of the electronic and electromechanical systems of Tesla electric cars to achieve the set goal. It includes a detailed analysis of the electronic stability control system, active pneumatic suspension, and electric power steering. Results. An analysis of scientific publications reveals that the problem of creating environmentally friendly and energy-efficient vehicles is currently being solved through the use of electric drives powered by traction batteries. Modern electric cars have overcome drawbacks such as low dynamics, limited range, and low maximum speed, surpassing similar internal combustion engine vehicles in these aspects. Tesla electric cars are currently the most technologically advanced and promising in this field. The analysis focuses on the technical solutions and advanced technologies employed in Tesla Model S electric cars, specifically the electronic stability control system, active pneumatic suspension, and electric power steering. The conducted research allows for an assessment of the current state of electronic and electromechanical systems in electric cars and provides insights into their future development. Originality. The results of this research provide a comprehensive understanding of the present state of electronic and electromechanical systems in Tesla electric cars. It enables a detailed analysis and exploration of the advanced technologies used in the development of Tesla electric cars and their distinctive features. Practical Value. The research findings contribute to identifying promising directions for the development of contemporary electronic and electromechanical systems in electric vehicles. They serve as a basis for creating recommendations concerning electronic stability control systems, active pneumatic suspension, and electric power steering, which can be valuable to scientific and technical professionals involved in the development of environmentally friendly vehicles.

Improving the Stability of Semi Trailer Articulated Vehicles

The transportation of industrial products is an important function of every industry involved in mass production. This is mostly done with the use of semi trailer articulated vehicles. The dynamics characteristic of these vehicles differs from those of other vehicles, and their accidents are fatal and destructive leading to lost of lives and valuable properties. Therefore, there is a need for continuous research and improvement of the stability of these vehicles. This paper aimed at reviewing literatures on improvement of stability of this vehicle in order to ensure safety of lives and properties. Driver Assistance Systems (DAS) such as Semitrailer Differential Braking Technique (SDBT), Roll Stability Control (RSC) system, Electronic Stability Control (ESC) system, Active Yaw Control (AYC) system, Linear Quadratic Regulator (LQR) controller, Robust LQR (RLQR), were noted as an efficient method for combating the vehicle instability and loss of control. It was noted that the RWA is an important parameter for determining the rollover propensity of this vehicle., while a driver model would be of great important to investigate the interaction between the driver and Driver Assistance Systems (DAS).

A Hierarchical Control Scheme for Adaptive Cruise Control System Based on Model Predictive Control

An adaptive cruise control (ACC) system can improve safety and comfort during driving by taking over longitudinal control of the vehicle. It requires the coordination between the upper-layer controller and the lower-layer actuators. In this paper, a hierarchical anti-disturbance cruise control architecture based on electronic stability control (ESC) system is proposed. The upper-layer controller outputs the desired longitudinal acceleration or deceleration to the lower-layer actuators. In order to improve the accuracy of model prediction and achieve the coordinated control of multiple objectives, an upper-layer model prediction cruise controller is established based on feedback control and disturbance compensation. In addition, based on the hydraulic control unit (HCU) model and the vehicle longitudinal dynamics model, a lower-layer nonlinear model predictive deceleration controller is proposed in order to solve the problems of pressure fluctuations and the low accuracy of small decelerations when ESC is used as the actuator for the ACC system. Finally, the simulation and experimental tests were carried out. The results show that the proposed control architecture can improve the stability and comfort of the cruise control process. Moreover, compared with the traditional PID deceleration controller, it effectively improves the deceleration control accuracy.

An autonomous emergency braking strategy based on non‐linear model predictive deceleration control

AbstractSurrogate safety measures (SSM) are used to assess the risk for autonomous emergency braking system (AEBS). Developing appropriate SSM and accurately executing the braking request are the key issues. Time‐to‐collision (TTC) is a typical time‐based SSM with limitations. By analyzing the braking process, this paper proposes a new SSM based on deceleration rate to avoid collision (DRAC). As the brake actuator, vehicle electronic stability control (ESC) system has many problems, such as large overshoot and pressure fluctuation. Considering the model of hydraulic control unit (HCU) and vehicle, a deceleration controller based on non‐linear model predictive control (NMPC) is proposed. Based on this, a layered AEBS architecture is proposed. The upper‐layer AEBS controller calculates the expected deceleration based on modified DRAC (MDRAC), and transmits it to the lower‐layer NMPC deceleration controller. Finally, the simulation and experimental tests are carried out. The results show that the system has a fast and stable response. In addition, the performance of the proposed AEBS strategy is tested according to the Euro‐NCAP test protocol. Comparing the results with the TTC method, the proposed method can improve the stability of the distance margin by more than 0.55 m, which ensures the safety and improves the stability of the vehicle.

A novel H∞ observer for sensor fault diagnosis of vehicle electronic stability control system with disturbance and input delay

This paper mainly focuses on the sensor fault diagnosis method based on H∞ observer in vehicle electronic stability control (ESC) system with disturbance and input delay. Firstly, the four-wheel steering vehicle model is established. Secondly, the system state and sensor fault are reconstructed into new system variables by a special matrix transformation method, based on which a new H∞ observer is developed to estimate system state and sensor fault signals. Then, based on Lyapunov method and linear matrix inequality (LMI) theory, the conditions for asymptotic stability and H∞ performance of the estimation error system are proved. Finally, Carsim and Matlab/Simulink co-simulation are used to show the effectiveness of the method.

Development of a hil-testbench for testing vehicles with an electronic stability control system

At the moment, in the industry (auto- and aircraft), the hardware-in-the-loop modeling (HIL) is actively used, to wit test object is simulated, and the control unit remains real, switching with the virtual world through a real-time device. This article presents a similar development of NNSTU engineers — a HIL-testbench designed to conduct "physical" virtual tests of vehicles equipped with an ESC system. Specialists have developed a mathematical model of the movement of the car, from which the C-code was successfully generated, which allows performing calculations in real-time on the developed testbench. The correctness and adequacy of modeling are proved by the conducted field tests of ESC systems. At the end of the article, the results of comparing virtual and field tests are presented. Keywords: HIL, ESC system, modelling, real-time, testing, verification

Vehicle Lateral Stability Regions for Control Applications

This article presents an improved method of obtaining lateral stability regions for road vehicles, considering the influence of steering angle, center of gravity, longitudinal speed, and tire-road friction coefficient on the vehicle dynamics. Comprehensive stability regions are obtained for a wide range of such parameters. Moreover, conservative stability regions are proposed, in the case of control applications that demand robust or safety-critical control actions. Next, a steering-angle-dependent region is used to implement a safety-critical electronic stability control system with active front steering as actuation. The resulting control system extends safety-critical control based on control-dependent barrier functions, introducing a control-dependent Lyapunov function to improve its steady-state behavior. Finally, we identify and propose workarounds for problems that arise from the number of inputs being less than the dimension of the desired safe set. The conservative stability regions and the extended safety-critical control system are validated by means of simulation results based on a nonlinear lateral stability model.

Rollover Index for Rollover Mitigation Function of Intelligent Commercial Vehicle’s Electronic Stability Control

This paper describes a rollover index for detection or prediction of impending rollover in different driving situations using minimum sensor signals which can be easily obtained from an electronic stability control (ESC) system. The estimated lateral load transfer ratio (LTR) was used as a rollover index with only limited information such as the roll state of the vehicle and some constant parameters. A commercial vehicle has parameter uncertainties because of its load variation. This is likely to affect the driving performance and the estimation of the dynamic state of the vehicle. The main purpose of this paper is to determine the rollover index based on reliable measurements and the parameters of the vehicle. For this purpose, a simplified lateral and vertical vehicle dynamic model was used with some assumptions. The index is appropriate for various situations although the vehicle parameters may change. As part of the index, the road bank angle was investigated in this study, using limited information. Since the vehicle roll dynamics are affected by the road bank angle, the road bank angle should be incorporated, although previous studies ignore this factor in order to simplify the problem. Because it increases or reduces the chances of rollover, consideration of the road bank angle is indispensable in the rollover detection and mitigation function of the ESC system. The performance of the proposed algorithm was investigated via computer simulation studies. The simulation studies showed that the proposed estimation method of the LTR and road bank angle with limited sensor information followed the actual LTR value, reducing the parameter uncertainties. The simulation model was constructed based on a heavy bus (12 tons).

Dynamic coordinated control strategy of autonomous vehicles during emergency braking under split friction conditions

In case of emergency braking in danger, autonomous vehicle usually uses electronic stability control system to maintain the dynamic stability of the vehicle, and by adjusting the steering system, the vehicle can realize autonomous driving. However, when the autonomous vehicle is in emergency braking on the split-mu road, due to the inconsistent adhesion coefficient on both sides of the road, the inconsistency of tire force will not only damage the dynamic stability, but also make the vehicle deviate from the planned trajectory. Because the path tracking algorithm of autonomous vehicle needs to detect the trajectory error first, it will lead to the time delay of trajectory error correction, and its correction ability will weaken with the decrease of speed, so that the vehicle's trajectory will deviate unilaterally. Thus, the tracking accuracy is reduced and the driving safety is endangered. This paper proposes a dynamic coordinated control strategy based on dynamics and kinematics. In response to the rapid changes in lateral disturbances, a flexible control transfer mechanism based on vehicle status is constructed, realize dynamic coordinated control based on path tracking algorithm and active steering algorithm. While improving the lateral stability, the trajectory error is reduced.

Safety systems and vehicle generations: Analysis of accident and travel data collected using event data recorders

The current paper proposes a data analysis method to evaluate the impact of vehicle-technology evolution on road safety based on a recent and extensive accident dataset (1.3 million vehicles in 2017 and 1.7 million in 2018, Italy). Seventeen models of vehicles equipped with an event data recorder were selected for acquiring data, including the distances travelled by the vehicles during the year, and were aggregated by their year of initial registration and model. This unique information in conjunction with the accident datasets enabled a consistent estimation of risk exposure and accident rates for various subsets of vehicles. Thereafter, the comparative analysis of accident rates revealed an improvement in the road safety along with a significant variation between various vehicle models that approximately ranged from 5–10 accidents per million kilometres. Moreover, the accident rate reduced after the electronic stability control system was mandated for vehicles in the market, exhibiting variations in the range of 15–30% for serious accidents that were dependent on the vehicle model. Further safety improvements were identified for the latest generation of vehicles equipped with more advanced technologies such as the autonomous emergency braking that can reduce the accident rate up to 38%.

A Comparative Study of Energy Consumption and Recovery of Autonomous Fuel-Cell Hydrogen–Electric Vehicles Using Different Powertrains Based on Regenerative Braking and Electronic Stability Control System

Today, with the increasing transition to electric vehicles (EVs), the design of highly energy-efficient vehicle architectures has taken precedence for many car manufacturers. To this end, the energy consumption and recovery rates of different powertrain vehicle architectures need to be investigated comprehensively. In this study, six different powertrain architectures—four independent in-wheel motors with regenerative electronic stability control (RESC) and without an RESC, one-stage gear (1G) transmission, two-stage gear (2G) transmission, continuously variable transmission (CVT) and downsized electric motor with CVT—were mathematically modeled and analyzed under real road conditions using nonlinear models of an autonomous hydrogen fuel-cell electric vehicle (HFCEV). The aims of this paper were twofold: first, to compare the energy consumption performance of powertrain architectures by analyzing the effects of the regenerative electronic stability control (RESC) system, and secondly, to investigate the usability of a downsized electrical motor for an HFCEV. For this purpose, all the numerical simulations were conducted for the well-known FTP75 and NEDC urban drive cycles. The obtained results demonstrate that the minimum energy consumption can be achieved by a 2G-based powertrain using the same motor; however, when an RESC system is used, the energy recovery/consumption rate can be increased. Moreover, the results of the article show that it is possible to use a downsized electric motor due to the CVT, and this powertrain significantly reduces the energy consumption of the HFCEV as compared to all the other systems. The results of this paper present highly significant implications for automotive manufacturers for designing and developing a cleaner electrical vehicle energy consumption and recovery system.

Development and Validation of Electronic Stability Control System Algorithm Based on Tire Force Observation

In view of the higher and higher assembly rate of the electronic stability control system (ESC in short), the control accuracy still needs to be improved. In order to make up for the insufficient accuracy of the tire model in the nonlinear area of the tire, in this paper, an algorithm for the electronic stability control system based on the control of tire force feedforward used in conjunction with tire force sensors is proposed. The algorithm takes into consideration the lateral stability of the tire under extreme conditions affected by the braking force. We use linear optimal control to determine the optimal yaw moment, and obtain the brake wheel cylinder pressure through an algorithm combining feedforward compensation based on measured tire force and feedback correction. The controller structure is divided into two layers, the upper layer is controlled by a linear quadratic regulator (LQR in short) and the lower layer is controlled by PID (Proportional-integral-derivative) and feedforward. After that, verification of the controller’s algorithms using software cosimulation and hardware-in-the-loop (HIL in short) testing in the double lane change (DLC in short) and sine with dwell (SWD in short) conditions. From the test results it can be concluded that the controller based on tire force observation has partially control advantages.

Performance Prediction and Flow Characteristics of a Hydraulic Pump for ABS and ESC Systems Using FSI Simulation

The electronic stability control (ESC) system is a computerized technology that improves vehicle stability by detecting and reducing the loss of traction. The hydraulic control unit for an anti-lock braking system (ABS) or an ESC system in a car includes a hydraulic pump located between the wheel and master cylinder. The function of the hydraulic pump is to allow the brake fluid to return from the wheel to the master cylinder when the ABS or ESC is actuating. This study performs numerical investigations with the aim of predicting the performance of the hydraulic pump by better understanding the dynamic behavior characteristics of the inlet ball under instantaneous fluid forces during the suction cycle and the corresponding flow characteristics under various motor speeds. A fluid-structure interaction (FSI) simulation of the hydraulic pump is conducted under various motor speeds with an unsteady three-dimensional approach considering laminar flow and the user-defined function (UDF). Experimental verification of the simulation results at the standard pump pumping test system of the Mando Corporation in Korea indicates considerable reliability. The findings of this research can provide valuable insights into designing high-efficiency pumps.

DESIGN AND ASSESSMENT OF A SPEED-BASED INTEGRATED ACTIVE VEHICLE CONTROLLER FOR LATERAL STABILITY

An integrated active vehicle control system implementing fuzzy-logic control (FLC) is introduced. The system integrates three commercially- available active vehicle control systems, namely, Active Front Steering (AFS), Electronic Stability Control (ESC) and Torque Vectoring System (TVS) aiming at enhancing vehicle handling and cornering stability and rollover prevention. Two different vehicle models were constructed to simulate the dynamic behavior of the system with and without the proposed integration controller, namely, a 14-DOF vehicle dynamic model with nonlinear tire characteristics and a 2DOF bicycle reference model. Last model was utilized to generate controller’s reference values of vehicle’s yaw rate and body side slip angle at a given forward speed and driver’s steering input. Simulation was carried out in the MATLAB/SIMULINK software environment. The effectiveness of the system was investigated applying five different standard cornering test maneuvers at different vehicle forward speeds of 10, 20 and 30m/s. Simulated test maneuvers are: step, J-turn, single lane change (SLC), sine with dwell, (SWD) and fishhook.Results reveal that, for stability enhancement, AFS is most effective at low vehicle speeds with declining efficacy as speed goes up. Both ESC and TVS have been found to be equally effective at moderate to high speeds. In conclusion, an integrated chassis control (ICC) strategy has been proposed that improves vehicle handling and cornering performance across the entire operating range of speed using a forward-speed-based stability criterion to allocate stability control authority and ensure smooth transition of control between the three AFS, ESC, and TVS systems.

Evaluating Model Predictive Path Following and Yaw Stability Controllers for Over-Actuated Autonomous Electric Vehicles

Active safety systems are of significant importance for autonomous vehicles operating in safety-critical situations like an obstacle-avoidance manoeuvre with high vehicle speed or poor road condition. However, a conventional electronic stability control system, may not always yield desired path following and yaw stability performance in such circumstances merely through brake intervention. This paper pursues a detailed investigation on utilising model predictive control (MPC) and torque vectoring for path following and yaw stability control of over-actuated autonomous electric vehicles (AEVs) in dangerous double lane change manoeuvre. The control problem of the AEV is formulated based on MPC by utilising active front steering and torque vectoring, and constraints are imposed explicitly on yaw rate and sideslip angle to ensure yaw stability. Four MPC-based controllers are designed based on double-track vehicle models. Specifically, they include two one-level controllers, i.e. one with torque vectoring and one with equal torque allocation, and two two-level controllers, i.e. one with optimisation-based torque allocation and one with rule-based allocation. These controllers are assessed extensively, with respect to passing velocity, tracking accuracy, tyre utilisation and robustness. The effect of horizon length on the control performance and computational efficiency is also investigated.

Advanced Vehicle Control With an Optimized Speed Profile Using Road Characteristics for Road Departure Prevention

Many passenger vehicles are equipped with automatic safety features. One system, Electronic Stability Control (ESC), saved 7,024 lives from 2011 to 2015. While effective, ESC and other similar control systems are reactionary in nature and require knowledge of a vehicle's current state to determine the response at the next state. Also, many control systems do not take the road characteristics into account, despite being an important contributor to a vehicle's dynamics. This work presents a predictive vehicle controller to help prevent roadside departures during cornering that incorporates the road's geometry and roughness to estimate the vehicle's safe operating speed. An Optimized Speed Profile generates a speed trajectory to allow the vehicle to successfully navigate the corner while preserving ride quality. Simulation results demonstrate cases in which vehicles equipped with ESC would depart from the road while the proposed system does not. Simulations demonstrate that road roughness effects account for up to 10% of the velocity changes in the maximum allowable cornering speed; simulations based on a real-world highway off-ramp measurement demonstrate that the proposed control system is capable of lane-keeping while maintaining stability.

Increasing efficiency of braking control algorithm for a two-wheeled motorcycle

The paper presents a new method for improving the efficiency of the braking control algorithm for a two-wheeled motorcycle. The method is based on the use of high quality information sources - direct measurement and analysis of forces in the wheel-road contact. The criterion for generating control signals by actuators is based on the negative sign of derivatives of lateral forces acting on wheels with respect to time. Experimental studies have shown that the negative sign of lateral force derivatives with respect to time determines side slip of wheels relative to the road surface. The consequence of the sideslip is loss of vehicle stability. The algorithm for generating vehicle control signals, which is based on the negative sign of the lateral force derivative with respect to time, is, to some extent, analogous to modern ESP systems (electronic stability control systems), which are currently being actively installed in two-wheeled vehicles (motorcycles).

Diagnosing Automotive Damper Defects Using Convolutional Neural Networks and Electronic Stability Control Sensor Signals

Chassis system components such as dampers have a significant impact on vehicle stability, driving safety, and driving comfort. Therefore, monitoring and diagnosing the defects of these components is necessary. Currently, this task is based on the driver’s perception of component defects in series production vehicles, even though model-based approaches in the literature exist. As we observe an increased availability of data in modern vehicles and advances in the field of deep learning, this paper deals with the analysis of the performance of Convolutional Neural Networks (CNN) for the diagnosis of automotive damper defects. To ensure a broad applicability of the generated diagnosis system, only signals of a classic Electronic Stability Control (ESC) system, such as wheel speeds, longitudinal and lateral vehicle acceleration, and yaw rate, were used. A structured analysis of data pre-processing and CNN configuration parameters were investigated in terms of the defect detection result. The results show that simple Fast Fourier Transformation (FFT) pre-processing and configuration parameters resulting in small networks are sufficient for a high defect detection rate.