Steering System Research Articles

Haptic tele-driving design of vehicle steering control system with communication delay under complicated driving and road conditions

Haptic tele-driving design of vehicle steering control system with communication delay under complicated driving and road conditions

Research on energy saving and control characteristics of back pressure controllable variable speed pump controlled steering system for heavy vehicles

Research on energy saving and control characteristics of back pressure controllable variable speed pump controlled steering system for heavy vehicles

Non-mechanical beam steering for high-speed optical wireless communications via electrowetting on dielectric.

Electrowetting on dielectric (EWOD) is used for non-mechanical optical beam steering (OBS) in optical communication systems. High-capacitance ion gel is used to construct an efficient electrowetting interface that facilitates dynamic OBS. This integration facilitates precise control of beam steering and data transmission efficiency in optical wireless communication systems. An EWOD-based liquid prism (LP) manipulates beam direction via electrowetting. The theoretical framework is supported by the Young and Young-Lippmann equations for precise optical path control. We present a theoretical and experimental demonstration of a two-dimensional beam steering system using an EWOD-based LP, with beam steering up to 14.82° and 14.39° along the X and Y axes, respectively. The system achieves data rates of 1.9 Gbps in free-space optics (FSO) and 1.7 Gbps in underwater wireless optical communication (UWOC) systems, with a measured bit error rate that adheres to the standard threshold of the forward error correction limit. Our results suggest that the EWOD-based LP system offers a compact, efficient, and versatile design for optical devices in both FSO and UWOC systems.

Flies tune the activity of their multifunctional gyroscope

Members of the order Diptera, the true flies, are among the most maneuverable flying animals. These aerial capabilities are partially attributed to flies' possession of halteres, tiny club-shaped structures that evolved from the hindwings and play a crucial role in flight control. Halteres are renowned for acting as biological gyroscopes that rapidly detect rotational perturbations and help flies maintain a stable flight posture. Additionally, halteres provide rhythmic input to the wing steering system that can be indirectly modulated by the visual system. The multifunctional capacity of the haltere is thought to depend on arrays of embedded mechanosensors called campaniform sensilla that are arranged in distinct groups on the haltere's dorsal and ventral surfaces. Although longstanding hypotheses suggest that each array provides different information relevant to the flight control circuitry, we know little about how the haltere campaniforms are functionally organized. Here, we use invivo calcium imaging during tethered flight to obtain population-level recordings of the haltere sensory afferents in specific fields of sensilla. We find that haltere feedback from both dorsal fields is continuously active, modulated under closed-loop flight conditions, and recruited during saccades to help flies actively maneuver. We also find that the haltere's multifaceted role may arise from the steering muscles of the haltere itself, regulating haltere stroke amplitude to modulate campaniform activity. Taken together, our results underscore the crucial role of efferent control in regulating sensor activity and provide insight into how the sensory and motor systems of flies coevolved.

High-dynamic steering control of the pump-controlled electro-hydraulic steering system for heavy vehicles with active disturbance suppression

Low-frequency response, strong nonlinearity and unknown disturbances are the main challenges faced by the engineering application of the pump-controlled electro-hydraulic steering systems (EHSSs) for heavy vehicles. To solve the above problems, an active disturbance suppression controller is proposed based on a variable rate reaching law (VRRL) and a terminal sliding mode observer (TSMO) in the framework of the sliding mode control. This controller is unique because, the VRRL introduces a nonlinear activation function, which enables smooth switching between multiple reaching rates, effectively improving the response speed and the disturbance rejection performance of the pump-controlled EHSS. Furthermore, an adaptive incomplete disturbance compensation control strategy is proposed by incorporating a TSMO to further improve the accuracy and robustness of the steering system, which employs a VRRL-based TSMO to realize accurate estimation of the lumped disturbance in finite time, and avoids controller overcompensation by selecting a preferred disturbance compensation coefficient. The stability analysis demonstrates that the proposed controller effectively suppresses the lumped disturbance and reduces the convergence domain of the steering system. A pump-controlled EHSS experimental bench is constructed, and a series of experiments are conducted with various steering frequencies and load conditions, which validate the ability of the proposed controller to achieve high-precision dynamic steering in all-terrain conditions of the pump-controlled EHSS for heavy vehicles.

Controllable region analysis of active front steering and differential braking system stability control characterized by additional yaw moment

Active Front Steering (AFS) and Differential Braking System (DBS) are commonly used execution systems for vehicle anti-rollover or handling stability control. They regulate the vehicle’s yaw moment by adjusting the lateral tire force and longitudinal tire force, respectively. However, these two systems differ in terms of control capabilities and regulatory sensitivities. In emergency conditions, it becomes crucial to allocate and coordinate the tasks for the execution systems according to their yaw moment control capability and adjustment sensitivity. This paper proposes a method for calculating the controllable region represented by the additional yaw moment. This method allows for the computation of the control capability of AFS and DBS based on the current state. Additionally, the influence of different vehicle states on the controllable regions of the two execution systems is analyzed. Building upon this analysis, the yaw moment adjustment sensitivities of AFS and DBS systems under the current state are further investigated. Finally, a task coordinated strategy between AFS and DBS is developed based on the analysis of controllable regions and sensitivities of different execution systems. Simulink simulations are conducted on yaw stability and roll stability conditions to comprehensively analyze the working process of the proposed task coordination strategy.

Decentralized control mechanism for limb steering in quadruped robot walking

Quadrupedal mammals adaptively change their direction, and their behavior is remarkable when they initiate such turns. They flexibly alter their interlimb coordination patterns when transitioning from forward to turning motion. However, the turning performance of quadruped robots is low compared to that of animals. We attempted to understand the control mechanism underlying the animal's flexible turning behavior by developing a simple robot model. We hypothesize that animals achieve lateral acceleration during transitions by adjusting the position of their limbs sideways at ground contact. On this basis, we proposed a decentralized control model for limb steering in quadrupedal turning behavior. The results obtained from the robot simulation demonstrated that either a turn initiated by the medial forelimb or the lateral forelimb occurred depending on the timing of the turn command. The fact that the proposed control algorithm could reproduce the behavior observed in animals suggests that a mechanism similar to the algorithm may exist in animals. Biological verification is expected in the future.

Fault Detection Methods for Electric Power Steering System Using Hardware in the Loop Simulation

The development of the automotive industry is associated with the rapid advancement of onboard systems. In addition, intensive development in the electronics and control systems industry has resulted in a change in the approach to the issue of assistance systems in vehicles. Classic hydraulic systems have been almost completely replaced by modern electric power steering (EPS) systems, especially in citizen vehicles. This paper focuses on fault detection algorithms for EPS, along with the available tools to aid development and verification. The article discusses in detail the current state of knowledge in this area. The principle of operation of the EPS system and the influence of the structure of the mechanical system on its operation, in particular the characteristics of the ground–tire contact, are presented. Various error identification methods are presented, including those based mainly on a combination of tests of real objects as well as those combined with modern hardware-in-the-loop (HIL) equipment and virtual vehicle environment software, enabling the development of new diagnostic methods, enhancing the security, reliability, and energy control in the vehicle. A review of the literature indicates that although many algorithms which enable fault detection at an early stage are described, their potential for use in a vehicle is highly limited. The reason lies in simplifications, including models and the operating EPS temperature range. The most frequently used simplification of the model is its linearization, which significantly reduces the calculation time; however, this significantly reduces the accuracy of the model, especially in cases with a large range of system operation. The need for methods to detect incipient faults is important for the safety and reliability of the entire car, not only during regular use but also especially during life-saving evasive maneuvers.

Enhancement of Yaw Moment Control for Drivers with Excessive Steering in Emergency Lane Changes

When a ground vehicle runs at high speeds, even a slight excess in the wheel steering angle can immediately cause the vehicle to slide sideways and lose control. In this study, we propose an active safety control system designed to address emergency situations where the driver applies excessive steering input and the vehicle speed varies significantly during control. The system combines the direct yaw moment (DYM) method with a steering saturation scheme that prevents excessive driver steering input from adversely influencing the front-wheel steering. Consequently, the control system allows the DYM to focus more on other stabilization tasks and maintain tire/road friction within its workable linear range. The implementation relies on a reference steering angle and a reference vehicle state, derived from a linear vehicle model considering tire/road friction limitations. When the driver’s steering angle and the system state deviate from these reference values, the control system intervenes by applying both the steering saturation scheme and DYM method. This ensures the front-wheel steering angle and system state remain close to the reference values. The control strategy is developed using the polytopic Linear Parameter Varying (LPV) technique and Linear Matrix Inequality (LMI) to account for the changes in vehicle speed. It is further enhanced with an input saturation technique based on a high-gain approach, which improves control utilization and system response during emergency situations. The advantages of the proposed control strategy are demonstrated through simulation results.

The effect of path curvature on the stability of reversing truck–semitrailer in the presence of feedback delay

Stability analysis of the low-speed reverse motion along clothoid curve is presented for the truck–semitrailer combination. The single-track kinematic model supplemented with the steering system and the lower-level controller is applied. A higher-level controller is designed to stabilise the reverse motion of the vehicle. Linear state feedback with time delay is used with feedforward term to force the vehicle to the desired path. The linear stability analysis is done by semi-discretization and D-subdivision methods to determine the optimal control gain setup. The effects of path curvature and time delay on the stability are investigated and verified via numerical simulations. Results are validated via experiments using a small-scale test rig.

Kalman filter-based sensor fusion for Ackermann steering mobile robots

Abstract Autonomous navigation technologies are continuously improving in terms of performance and safety. A key subfield of autonomous navigation for mobile robots is localization or precise positioning, involving the robot understanding its position relative to key points of interest in the environment. Traditionally, localization is purely dependent on the quality of input received from onboard sensors and therefore localization quality degrades in the presence of high sensor error or other faults. Sensor fusion is useful to combat this. Sensor fusion is used to combine various data types from different sensors to gain a lower overall uncertainty or error in the resulting data, when compared to the separate data from each individual sensor. In this study a four-wheel mobile robot with front-wheel driving and steering is localized during navigation. The investigation is performed in simulation and with a physical prototype. The mobile robot has several sensors including a wheel encoder on each wheel, an inertial measurement unit as well as an indoor GPS system. A designed Kalman Filter called The Combined Kalman Filter has been designed to fuse the sensor input data in order to output the position data required to localize the robot in (X, Y) cartesian coordinates. This is completed in the presence of sensor bias error and noise with the output path compared against a pre-selected ground truth trajectory. The proposed filter is based on the Extended Kalman Filter to contend with the non-linear model arising from the four-wheel steerable robot with the steering system following the Ackermann steering condition. The robot model and sensors are simulated in MATLAB for a chosen ground truth trajectory with results highlighting any detected faults and final accurate position information. It was seen that the estimated filter output had high accuracy when compared with the ground truth. Compared with other investigations the proposed filter has reduced mean error and minimal deviations compared with the ground truth path. In addition, this filtering model can be used in general for the localization of other actuated steering vehicles and aims to widen the research in this field as the majority of research in this area leverages differential drive robots which require less complex modeling.

Improved Adaptive Feedforward Controller Based on Internal Model Principle with Disturbance Observer for Laser-Beam Steering Systems

This study presents an effective control algorithm to improve the robustness of fast steering mirror (FSM)-based laser-beam steering systems against dynamic disturbances, such as repetitive disturbances resulting from operating conditions. A stable control system must be able to maintain the required high-precision control, even when dynamic disturbances affect the FSM system. In this study, an improved control method is proposed using an internal model principle (IMP)-based nonlinear controller with a disturbance observer (DOB) for the FSM system. This IMP-based controller with DOB can attenuate the residual control-error signal under dynamic disturbance conditions.

Non-mechanical steering of the optical beam in spectral-domain optical coherence tomography

We demonstrate in a proof-of-concept experiment spectral-domain optical coherence tomography where steering of the optical beam that probes the sample in a transverse scan does not make use of any mechanical element. Steering is done with the help of a phase-only spatial light modulator, that introduces a spatially-dependent phase between the two orthogonal polarization components of an optical beam, and some optical elements that control the polarization of light. We demonstrate that making use of the non-mechanical beam steering system considered here, we can reproduce the main traits of imaging with standard OCT that makes use of mechanical-assisted optical beam steering.

The “negative income tax” as a steering mechanism: the semantic field of the NIT around Milton Friedman in his pre-monetarist period (1939–1948)

This paper explores the intellectual history of Universal Basic Income (UBI), specifically focusing on Milton Friedman’s Negative Income Tax (NIT) as a precursor. Examining Friedman’s work in the 1940s, the study reveals the polysemic nature of early NIT proposals and underscores the significance of Friedman and Stigler’s engagement with concepts like Abba P. Lerner’s Social Dividend and Kenneth Boulding’s adjustable tax plan, the latter often overlooked in the literature. Contrary to the prevailing view of NIT as solely a poverty alleviation policy, this research also positions it, at this moment, as a macroeconomic steering mechanism. Drawing on Reinhart Koselleck’s categories, theoretical analysis emphasises the importance of exploring diverse “layers of meaning” in early NIT debates, shedding light on nuances that echo contemporary discussions on UBI.

Design and Implementation of Closed-Loop Control of Vector Force in Static Push-the-bit Rotary Steering System

Design and Implementation of Closed-Loop Control of Vector Force in Static Push-the-bit Rotary Steering System

Electro-hydraulic SBW fault diagnosis method based on novel 1DCNN-LSTM with attention mechanisms and transfer learning

The Electro-hydraulic Steer-by-Wire (EH-SBW) is the future trend of commercial vehicle steering systems due to their dual actuator redundancy. The accurate fault diagnosis of the EH-SBW is an important basis for ensuring the safety of commercial vehicles. However, due to the strong coupling between dual actuators, rapid load changes and difficult sampling lead to the difficulty of existing techniques to meet the fault diagnosis of EH-SBW. Therefore, we propose the EH-SBW fault diagnosis method based on novel 1DCNN-LSTM with attention mechanisms and transfer learning, which contains a fault type diagnosis neural network (FTDNN) model and a fault degree estimation neural network (FDENN) model. The steering feature extractor (SFE) in the FDENN model fuses the driver’s long time-domain driving trend signals and the short time-domain signals from the steering system to extract the feature map, so that the feature map have more valid information in the case of fast load changes. Based on the result of the FTDNN and the feature map, the scaling attention layer in the FDENN amplifies the features that are favourable to the fault degree estimation accuracy and suppresses the expression of unfavourable features, which reduces the impact of strong coupling relationships on the fault degree estimation accuracy. The dynamic sample allocation strategy performs transfer learning of the SFE and scaling attention layer through a small number of samples, which enables the FDENN model to effectively estimate the degree of failure of the hydraulic mechanism. The experimental results show that the diagnostic accuracy of the proposed method is 94% when the electric mechanism fails. The diagnostic accuracy of the proposed method is 92% when the hydraulic mechanism fails.

Seven‐degree‐of‐freedom‐based electric wheel sampled‐data active shimmy control method considering unknown sensor measurement error

AbstractThe active shimmy control methods for electric vehicle driven by in‐wheel motors (EV‐DIM) have been proposed in the recent years. However, these methods assume that data obtained from sensors are accurate, despite the fact that sensor measurements are prone to error. This unknown measurement error can make shimmy control difficult. Additionally, current shimmy models are low degree‐of‐freedom, which simplifies control but decreases accuracy. In this paper, we address these issues using a sampled‐data output control method based on a higher seven‐degree‐of‐freedom (7DOF) shimmy model which includes the steering system, suspension, and electric wheel. We first construct a 7DOF electric wheel shimmy model and use Lagrange's theorem to derive the electric wheel shimmy dynamic equations. We then obtain system state equations that account for unknown sensor measurement error based on the 7DOF shimmy model. A sampled‐data observer and controller are designed to attenuate or eliminate the shimmy phenomenon via a domination gain. Finally, we conduct numerical simulations and experiments to verify the effectiveness of our proposed method.

Diagnosis-based design of electric power steering system considering multiple degradations: role of designable generative adversarial network anomaly detection

Abstract Recently, interest in functional safety has surged because vehicle technology increasingly relies on electronics and automation. Failure of certain system components can endanger driver safety and is costly to address. The detection of abnormal data is crucial for enhancing the reliability, safety, and efficiency. This study introduces a novel anomaly-detection method of designable generative adversarial network anomaly detection (DGANomaly). DGANomaly combines the data augmentation method of a designable generative adversarial network (DGAN) with a generative adversarial network anomaly-detection data classification technique. DGANomaly not only generates virtual data that are challenging to obtain or simulate but also produces a range of statistical design variables for normal and abnormal data. This approach enables the specific identification of normal and abnormal design variables. To demonstrate its effectiveness, the DGANomaly method was applied to an electric power steering (EPS) model when multiple degradations of gear stiffness, gear friction, and rack displacement were considered. An EPS model was constructed and validated using simulation programs such as Prescan, Amesim, and Simulink. Consequently, DGANomaly exhibited a higher classification accuracy than the other methods, allowing for more accurate detection of abnormal data. Additionally, a clearer range of statistical designs can be obtained for normal data. These results indicate that the statistical design variables that are less likely to fail can be obtained using minimal data.

Information Resilience in Networks: An Analysis of a National Security Legislation Evidence Base

Governance theory emphasises that networks are pivotal to societal governance and related steering mechanisms. One important means of steering is legislation, the evidence base of which is built on the interaction between social actors and the expert hearings related to the legislative process. This research uses network analysis to examine the construction of a legislative knowledge base and the information resilience displayed in the related networks. The data are derived from experts (n=440) appearing in committee hearings on five proposed acts of parliament. The results show that the expert consultations behind the legislation are official-oriented and illuminate the limited information produced by the private sector and a narrow view of scientific expertise. The network reveals epistemic authorities – mainly representing the security cluster – acting as gatekeepers. A more systemic approach is needed to build an evidence base encompassing the views on societal phenomena derived from different disciplines.

Analysis of consumer preferences for new electric vehicle technologies: Can future vehicle steering system steer consumer's purchase intention?

As the mainstream of vehicle industry is moving from internal combustion engine vehicles to electric vehicles (EVs), a multi-perspective analysis of consumer preference for the new EV technology is required. Therefore, this study proposes a new framework for consumer preference analysis—a two-stage choice experiment—and conducts an empirical analysis of the four-wheel independent steering system (4-WISS). In the first stage, we analyzed consumer preference for the availability of 4-WISS in EVs. In the second stage, we investigated consumer preference for the specific technology of 4-WISS in EVs. Stated preference data were collected through a choice experiment survey, and a mixed logit model was used to quantitatively analyze consumer preference and willingness-to-pay. Results show that consumers are willing to pay KRW 19,045,098.6 (USD 13,513.9) to use 4-WISS in high-end EVs. Furthermore, consumers who are female, older, and have more knowledge of autonomous vehicles prefer 4-WISS more. We found that consumers prefer the parallel movement among 4-WISS modes, the touch display for selecting 4-WISS, the steering wheel for operating 4-WISS mode, and dashboard for displaying information. We finally discuss the new business model in the vehicle industry and suggest automakers to establish an effective strategy for the initial market for EVs with 4-WISS.