Browse Topic: Electronic steering control

Items (12)
Road departures remain a major cause of fatal accidents in passenger vehicles, especially on highways, driving the demand for robust and affordable active safety technologies. Conventional Road Departure Mitigation Systems (RDMS) typically depend on camera- or LiDAR-based sensing, which can be cost-prohibitive and challenging to integrate across diverse vehicle platforms. The available RDMS technologies in the market focuses on road departure detection, and lacks the mitigation strategy. Although existing RDMS solutions have enhanced vehicle safety, their dependency on expensive, specialized sensors limits broader adoption, particularly in cost-sensitive market segments. This study introduces a sensor-less, cost-effective RDMS technology which has two parts, detection and mitigation. The technology utilizes existing vehicle sensors accessed through vehicle CAN channels. A decision tree based logic algorithm processes key parameters such as vehicle speed, steering angle, yaw rate, and lateral acceleration to detect potential unintentional road departure events. Upon detection, the system initiates a two-stage mitigation strategy: a driver alert followed by automatic corrective steering through the Electric Power Assisted Steering (EPAS) system, ensuring the vehicle remains within lane boundaries. The proposed methodology has been validated both digitally and at vehicle level, demonstrating functional robustness across a variety of driving conditions. This approach offers a scalable, affordable, and easily deployable solution for enhancing vehicle safety without the need for additional hardware investments.
Iqbal, ShoaibAdsul, Sourabh
Rack load estimation during the pre-design stages is critical for the calibration of steering systems, particularly in achieving the desired steering feel and optimizing assistance strategies in Electric Power Assisted Steering (EPAS). Conventional approaches often depend on physical vehicle testing or simplified empirical equations, which may be time-consuming or lacks the fidelity required for early-stage analysis. This paper presents a 1D simulation strategy to address limitations from conventional approaches. The proposed rack force estimation model is based on multi-physics analytical equations that calculate tire-road friction forces and the resulting moments about the steering axis, delivering a physics-based yet computationally efficient solution. The rack force estimation model is further extended into EPAS system model by incorporating Direct Current (DC) brushed motor model. The rack force estimation model is validated against physical test data which demonstrates a high level of accuracy. Finally, the EPAS motor sizing strategy is discussed to obtain the optimum motor size. The proposed simulation based approach enables engineering teams to make informed design decisions and optimize steering system behavior before physical prototypes are available.
Adsul, SourabhIqbal, Shoaib
The steering system of an automobile serves as the initial point of contact for the driver and is a crucial determinant in the purchasing choice of the vehicle. The present steering system is equipped with a singular Electric Power Assisted Steering (EPAS) map, resulting in a consistent steering sensation during maneuvers conducted at both low and high velocities. Certain vehicles are equipped with a steering system that includes fixed driving modes that require manual intervention. This paper presents a proposed Machine Learning based Adaptive Steering System that aims to address the requirements and limitations of fixed mode steering systems. The system is designed to automatically transition between comfort and sports modes, providing users with the desired soft or hard steering feel. The system utilizes vehicle response to driver input in order to identify driving patterns, subsequently adjusting steering assist and torque automatically. The system consists of driving pattern recognition module which classifies driver intention into sport or comfort driving. The system functionality is supported by the existing vehicle CAN data executing in real-time. Decision tree algorithm is employed to classify the driving patterns, with a physical data based accuracy rate of 98%. Additionally, mode holding logic is introduced in the system to avoid fluctuations between the two modes. The system has been effectively validated through the execution of maneuvers such as double lane changes and high-speed cornering both in digital and physical domains.
Deore, DhruvIqbal, ShoaibBhambri, MihirSheth, MalavSalunkhe, Swapnil
The steering system is to provide the driver with the possibility of lateral vehicle guidance, i.e. to influence the lateral dynamics of the vehicle; moreover, it is crucial to promptly translate the steering input to have the vehicle in high-quality directional stability. An electrical power assisted steering (EPAS) system is the sophisticated variant to meet higher requirements for vehicle safety, ride comfort, and driver-assist. This research is to investigate if a CAE methodology could be innovated to better simulate the durability of a steering system under various working scenarios; figure out the critical features of the modeling; conduct a correct analysis procedure for validating the modeling and collecting data for evaluation. With step by step in modeling and analysis, a well-established example of CAE model of EPAS is enabled to highlight the novelty of steering vehicle level CAE methodology and therefore achieve the research goal.
Song, GavinWou, Jason S.Rolls, ChristopherVlademar, Michael
In electric power assisted steering system (EPAS), the steering assistance torque is provided by the electric motor. The motor rating is decided based on rack force requirement which depends on the vehicle weight, steering gear ratio, wheel angles etc. The load on the EPAS motor varies with respect to the steered angles of the road wheels. The motor experiences higher load towards the road wheel lock position. Most of the steering systems used on passenger cars has rack and pinion gear with constant gear ratio (C-factor). The constant gear ratio is decided to create right balance between vehicle handling behavior and steering effort. The constant gear ratio exerts higher steering load which the EPAS motor is required to support up to road wheel lock angles and hence EPAS motor size increases. This paper presents variable gear ratio (VGR) steering system in which gear ratio varies from center towards end lock stroke of rack & pinion. The VGR is optimized for thermal performance through simulation in such a way that the steering system demands lower power from the column type EPAS(C-EPAS) motor during the static full lock operation. Simulation competency is developed in AMESIM® software for thermal performance prediction and then several digital iterations were performed for optimizing VGR of steering system. Based on simulation results, prototype vehicle was prepared with VGR rack and pinion with reduced size EPAS motor. Physical testing results are observed to be in-line with those predicted by digital model. The study resulted in reduction of EPAS motor size by optimizing the VGR without affecting the steering performance with additional benefit of system cost optimization.
Kulkarni, Parag VijayIqbal, ShoaibSalunkhe, SwapnilJoshi, NikhilShabadi, Nischalkumar
This paper is an application of ISO 26262 functional safety standards for fail-safe design, development and validation of Electric Power Assisted Steering (EPAS) System. As part of safety feature to save lives, prevent injuries and reduce economic loss due to accidents, many research institutes are working to ensure the safety and reliability of emerging safety-critical Electronic Control Systems in automobile applications. As, Advanced Driver Assistance Systems (ADAS) and other emerging technologies are introduced in the automobile application, the overall safety of these advanced electronic systems relies on the vehicle safety systems, such as steering systems. This paper outlines the approach of performing the Hazard Analysis & Risk Assessment (HARA) and developing a Functional Safety Concept. This approach incorporates several analysis methods, including Hazard and Operability study, Functional Failure Modes and Effects Analysis. This approach is then applied to the Electric Power Assisted Steering (EPAS) system to identify vehicle-level hazards, and derive safety goals and functional safety requirements. This paper presents the vehicle-level hazards, and safety goals derived from the analysis and includes a discussion of “fail-safe” and “fail-operational” needs, which results in the derivation of functional safety requirements. The results of this study may serve as an example of how different analytical methods could be applied to develop a functional safety concept.
Tikar, Sagar S.Ansari, Ashfaque
Many new vehicles come equipped with Advanced Driver Assistance Systems (ADAS) as standard or optional features. These technology packages frequently include Lane Departure Warning (LDW), an electronic system designed to alert the driver when the vehicle begins to depart from its lane. These systems identify lane boundaries using computer analysis of video captured by a forward-facing camera, typically mounted near the rear-view mirror. Some vehicles are also equipped with Lane Keeping Assist (LKA). Upon detecting an unintended lane departure, LKA will make electronic steering and/or braking control inputs to keep the vehicle in its original travel lane. Four vehicles equipped with LDW and LKA were tested: a 2019 Toyota Corolla, 2019 Honda Civic, 2020 Ford Explorer, and 2019 Chevrolet Tahoe. Tests were conducted on a straight, flat road with clear lane markings. Lane departures to the left and to the right were initiated by the test driver at 45 and 65 mph. Using a VBOX 3i RTK DGPS, data related to the vehicle’s speed, acceleration, and driver- and software-related control inputs were collected via the vehicle’s CAN bus. Additionally, the VBOX collected vehicle location data of ±2 cm (±0.79 in) accuracy relative to survey points. Analysis of test data yielded details of system-level behaviors. For LDW, the average warning issue point (lateral distance prior to reaching the lane boundary) observed was 1.33 ft, the average rate of departure (lateral velocity) was 1.45 ft/s, and the warning occurred 0.76 sec before lane departure. Lane keeping actions began, on average, 1.13 ft from the lane boundary (0.66 sec before lane departure) and involved 4.81 degrees of steering with an average maximum lateral acceleration of 2.86 ft/s2 (0.09 g). The LKA systems tested permitted the vehicles’ outside tires to exceed the lane boundaries by an average of 0.14 ft.
Nguyen, BenjaminFamiglietti, NicholasKhan, OmarHoang, RyanSiddiqui, OmairLanderville, Jon
In this study, a model of Active Front wheel Steer (AFS) system are developed and tested. In addition, an Integrated Dynamics Control with Front steer (IDCF) controller is also designed to investigate the performance of AFS system when it is integrated with a brake system. The IDCF system composed of an AFS system and a DYC (Direct Yaw moment Control) system of rear wheels. The AFS controller and IDCF controller are compared under several driving and road conditions with and without braking input and steering input. A 8 degree of freedom vehicle model is also employed to test the controllers. The results show that the model of AFS system shows good kinematic steering assistance function. Steering ratio varies depends on vehicle velocity between 12 and 24. Kinematic stabilization function also shows good performance because yaw rate of AFS vehicle tracks the reference yaw rate. IDCF shows improved responses compared to AFS because body side slip angle is also reduced regardless of road condition, steer input and brake input. These results represent that IDCF enhances lateral stability and steerability. Results also prove that AFS system shows satisfactory result when it is integrated with another chassis system. On a split-μ road, two controllers forced the vehicle to proceed straight ahead.
Song, Jeonghoon
This recommended practice is specifically limited to tractor scrapers, wheel loaders, wheel tractors, graders, and dumpers (as defined in SAE J1116 (January, 1977) and J1057a (June, 1975)) which are designed to operate at a maximum rated speed in excess of 20.0 km/h (12.4 mph) and which employ power source(s) in addition to the operator control effort to effect machine steering.
Off-Road Machinery Technical Comm
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