Browse Topic: Stability control

Items (467)
This article presents a cross-layer framework that integrates realistic vehicle-to-network-to-vehicle (V2N2V) delay characterization with a rigorous stability analysis of automated vehicle steering control. Both constant and network-induced time-varying delays modeled via deterministic bounds are addressed. For constant delays, delay-independent stability regions within the controller gain space are analytically derived. For time-varying delays with stochastic network origins, modeled using deterministic bounds, a refined Lyapunov–Krasovskii functional (LKF) incorporating augmented single- and double-integral terms is constructed. To establish delay-dependent linear matrix inequality (LMI) conditions, a reciprocally convex combination approach is employed to handle the delay interval partitioning, and the second-order Bessel–Legendre inequality is applied to tighten the integral quadratic bounds. The resulting LMI conditions explicitly capture the coupled effects of delay magnitude, delay variation rate, and control gains on closed-loop stability. Simulations of a lane-keeping scenario confirm that the predicted stability boundaries accurately match the closed-loop system behavior. Notably, incorporating a realistic time-varying V2N2V delay profile into the controller design reduces the lateral-state root-mean-square error (RMSE) by over 54% and decreases the settling time by a factor of 10 compared to designs relying on an average-delay assumption. However, high packet loss rates are shown to still induce residual oscillations due to information scarcity. Ultimately, these results elucidate delay-induced instability mechanisms and provide practical guidelines for designing delay-robust steering controllers for connected and automated vehicles.
Li, JialinLu, JianweiWei, HengAo, Di
Distributed drive electric vehicles (DDEVs) provide enhanced maneuverability through independent wheel torque control, but coordinating precise path tracking with lateral stability remains challenging under aggressive driving conditions. This paper presents a coordinated control strategy that integrates model predictive control (MPC) for path tracking with a proportional gain controller for stability regulation. The proposed framework adopts a hierarchical design. The path tracking control leverages MPC to compute front steering commands while accounting for vehicle dynamics and preview errors. The stability adjustment uses dual proportional gain controllers to generate an additional yaw moment, which is adaptively balanced through a phase plane coordination mechanism, enhancing yaw stability during path tracking. The generated yaw moment is subsequently distributed to individual in-wheel motors with an optimization torque allocation method, respecting tire force limitations. The effectiveness of the proposed strategy is validated with hardware-in-the-loop (HIL) experiments under a double lane change maneuver. Results show that the coordinated approach improves path following and maintains yaw stability more effectively than conventional methods.
He, YangZhu, YuzhengGuo, RuixinZhu, YueyingXing, ChaoLiu, ShuangxiLin, Yier
Corner module vehicles (CMVs) achieve the decoupling of driving, braking, steering, and suspension, significantly enhancing vehicle handling potential, but under extreme operating conditions, the interactions between actuators severely constrain the improvement of vehicle handling performance. In order to mitigate conflicts between subsystems and enhance vehicle handling stability, a hierarchical hybrid game–based limit stability control method for CMVs is proposed in this article. Taking into account the handling potential of subsystems under limit conditions, a Stackelberg leader–follower game is designed by first designating Direct Yaw moment Control (DYC) as the leader and Active Rear Steering (ARS) as the follower. Subsequently, the DYC–ARS and Active Suspension System (ASS) were constructed into a non-cooperative game system, and the Nash equilibrium solution was solved through iteration. The lower-level controllers, respectively, established a tire force distribution model that minimizes the overall tire utilization rate and an active suspension force distribution model that does not affect the vehicle’s pitch, in order to enhance the safety margin of the vehicle under extreme conditions. Finally, the Hardware-in-the-Loop test results proved the effectiveness of the proposed controller.
Peng, JinxinXiao, FengKe, YuanJin, Liqiang
To improve the handling stability of four-wheel steering/drive vehicles under complex high-speed maneuvers, this study proposes a coordinated control strategy that incorporates Active Rear Steering (ARS) and Direct Yaw Moment Control (DYC) based on a dynamic stability region. Firstly, a four-wheel steering vehicle dynamics model including lateral motion and yaw motion is established, and the ideal values of the control variables are determined. Secondly, combined with the fuzzy control theory and double-line method, the boundary of the dynamic stability region is obtained in the sideslip angle-sideslip angle rate β−β̇ phase plane, and the vehicle state is categorized into stable, unstable, and critical stable region. Then, A hierarchical control architecture is designed based on the stability boundary. The upper controller comprehensively solves the target rear wheel angle and additional yaw moment through feedforward feedback control; the coordinated control layer allocates control weights according to the stable state of the vehicle; the lower controller optimizes torque distribution through quadratic programming. Finally, the control strategy is validated by MATLAB/Simulink and CarSim co-simulation platform. The results show that the proposed control strategy reduces the RMS values of yaw rate and sideslip angle by 23.1% and 28.5% respectively, significantly improving the handling stability of the vehicle.
Nie, KeheChen, JinWang, FalongLi, RenBai, Xianxu
This study investigated the feasibility of using Deep Reinforcement Learning (DRL) for aeroelastic stability control of a Tiltrotor Aeroelastic Stability Testbed (TRAST) model. The DRL controllers use rotor swashplate inputs to minimize oscillatory wing root bending moments of the tilt rotor model. First, three DRL-based agents including Deep Deterministic Policy Gradient (DDPG), Twin Delayed Deep Deterministic Policy Gradient (TD3), and Soft Actor-Critic (SAC) were investigated to control the aeroelastic stability of the TRAST model throughout a wide range of airspeed including where the whirl flutter occurs. All three agents demonstrated the capability of stability augmentation while the SAC agent demon-strated the most robust performance. Next, the effectiveness of the SAC agent was studied further by training the SAC agent at a certain airspeed and applying the trained agent through the TRAST whirl flutter conditions. Finally, additional tuning of the SAC agent was performed to improve performance further through a hyperparameter optimization framework called Optuna.
Husain, SyedFloros, MattAnusonti-Inthra, PhuriwatKang, Hao
This paper presents a testing platform for the development of lateral stability control systems in independent motor electric vehicles (EVs). A 10 degree of freedom (DOF) vehicle simulation and a radio control test vehicle are constructed to enable controls validation scalable to full size vehicles. These vehicle simulations, or ‘digital twins’, have been widely adopted throughout the automotive industry due to their lower operating costs and ease of implementation. Virtual models are not perfect representations of reality, however, and physical testing is still necessary to validate systems for use in the real world. This is especially true when testing safety-critical features such as stability control. As a result, a simulation environment working in conjunction with a test vehicle represents an optimal hybrid approach. In this work, a high fidelity vehicle model is constructed in the Matlab/Simulink environment. To capture the effect of suspension, the digital twin is capable of modeling all angular and linear degrees of freedom of the vehicle body. The vehicle model must also estimate wheel forces during high-sideslip maneuvers. The Pacejka Magic Formula is used for its accurate representation of tire behavior in highly transient driving scenarios. This vehicle model describes the behavior of a physical vehicle. For this purpose, a 1/5 scale radio controlled vehicle with independent rear wheel propulsion is designed and assembled. All physical parameters of the test vehicle required by the vehicle model are estimated through direct measurement or estimation through test maneuvers. Magic formula coefficients are estimated from GPS, inertial, and odometry measurements collected throughout defined test maneuvers. Vehicle model behavior is then benchmarked against the test vehicle. An S-curve maneuver is performed in simulation and experimentation to ensure accuracy and consistency across transient and steady state behavior. In future work, focus will turn to creating an ADAS control system which re-stabilizes a vehicle after a collision using torque vectoring.
Petersen, Nicholas ConnerRobinette, Darrell
Federal Motor Vehicle Safety Standards (FMVSS) 126 and 136 are standards imposed on four of the eight recognized road vehicle classes in The United States. These standards make it mandatory for Electronic Stability Control modules (ESC) to be mounted to Class 1,2,7, and 8 vehicles. These modules strategically activate the vehicle brakes via the Antilock Brake System (ABS) to limit the recorded yaw rate and lateral displacement of a vehicle during an extreme cornering maneuver such as a sudden swerve to avoid an obstacle on the road. The two aforementioned FMVSS mandates also specify three different driving maneuvers that are conducted to profile and analyze ESC module performance. There is now an interest in creating a new FMVSS that makes ESC modules mandatory for Class 5 vehicles. The purpose of this paper is to analyze how one specific Class 5 vehicle’s ESC module performed when subjected to the two test procedures that correspond to FMVSS 126 and 136. As will be seen, the vehicle’s ESC performed quite well for the FMVSS 126 testing criteria and not as well with the FMVSS 136 testing criteria. The details of these results should both be considered if and when a new FMVSS ESC mandate is to be produced. To aide in the creation of such a mandate, additional experimental and simulation data will be necessary from other Class 5 vehicles. Simulated driving maneuvers with an accurate vehicle model will prove valuable in this pursuit. The results of such simulations will be discussed and the value that they bring will help to expedite the formation of the proposed FMVSS that covers these vehicles.
Cazares, Richard IsaacGuenther, DennisHeydinger, Gary
Vehicles may enter highly unstable dynamic states due to lateral collisions, sudden loss of grip, or extreme steering disturbances. When such instability arises in congested road sections where obstacle avoidance is required, the safety risk to both the ego vehicle and surrounding traffic escalates significantly. In such scenarios, the vehicle must not only regain stability but also navigate the roadway in the shortest feasible time to prevent secondary collisions. This paper investigates the minimum-time maneuver of a vehicle starting from an unstable dynamic condition and constrained to travel within prescribed road boundaries. A single-track vehicle model with combined-slip nonlinear tire model is employed to capture the vehicle dynamics under high slip conditions. Phase-plane analysis is conducted to reveal how control inputs reshape the system’s vector field and influence the possibility and speed of stability recovery. An optimal control problem is formulated to compute the minimum-time control sequence subject to both dynamic and kinematic constraints, actuator limits and road boundary constraints. The optimal control problem accounts for both stabilization and rapid progression through the constrained road segment. Simulation results on straight and curved road sections show that the minimum-time maneuver consistently exhibits a two-stage structure. The vehicle initially undergoes a stabilization phase, characterized by spiral convergence in the (β, r) phase plane. After stability is restored, the optimal maneuver transitions into the second phase where the vehicle follows the minimum-time trajectory dominated by the road geometry. The findings suggest that, in emergency scenarios, stability recovery should be prioritized before attempting aggressive avoidance or cornering maneuvers.
Leng, JiatongYu, LiangyaoWang, YongxinYou, WeijieLi, ZiangJin, Zhipeng
To enhance the lateral stability of four-wheel-drive intelligent electric vehicles (FWDIEV) under extreme operating conditions, this paper proposes a cooperative control strategy integrating active front steering (AFS) and direct yaw moment control (DYC) based on dissipative energy method. A nonlinear three-degree-of-freedom vehicle model is established to analyze the evolution of the vehicle state phase trajectory. A quantitative lateral stability index is constructed using dissipative energy to accurately evaluate the vehicle’s lateral dynamics. Utilizing dissipative energy and its gradient information, a time-varying stability boundary is defined under dynamic constraints, and adaptive weighting coordination between the AFS and DYC systems is designed to achieve coordinated control of front steering angle and additional yaw moment. A feedforward–model predictive control (FF-MPC) framework is developed, in which a feedforward module generates compensation based on driver intent to improve system responsiveness, while the model predictive controller predicts real-time vehicle states and optimizes the front steering angle and yaw moment control inputs. This enables cooperative tracking of the yaw rate and sideslip angle, effectively suppressing lateral motion errors. Furthermore, an optimal torque distribution strategy is formulated with the objective of maximizing tire–road friction utilization, incorporating constraints such as tire load rate and motor output capability to prevent wheel slip and improve handling stability. The effectiveness of the proposed control strategy is validated through both CarSim/Simulink co-simulation and real vehicle tests under typical maneuvers such as high-speed double lane change on various road surfaces. Results demonstrate that the proposed method significantly reduces tracking errors in yaw rate and sideslip angle compared to conventional MPC strategies, thereby enhancing lateral stability and ensuring driving safety under extreme conditions.
Zhao, KunZhao, ZhiguoWang, YutaoXia, XueChen, XiHu, Yingjia
Electric vehicle chassis integration control aims to improve vehicle handling and comfort. Previous studies encountered significant practical limitations, such as computational overhead in real-time execution scenarios. Designing effective and efficient algorithms for actuator coordination remains challenging. This article presents a synergetic controller for chassis coordination, combining fuzzy logic and stability region theory. First, the controller targets are the yaw rate and side slip angle, which are obtained from a highly accurate multi-body dynamic model. In addition, based on the generated fuzzy rules, the system calculates the required additional yaw moments for each actuator and optimizes their output. Then, the designed controller can distribute control effort optimally in real-time between braking and rear-wheel steering based on the stability status of the vehicle. Furthermore, a stability factor approach is used to formulate a dynamic safety strategy executed by the chassis. It helps to create the safety boundary of the vehicle and avoid excessive force and angle of execution. Finally, real-vehicle tests are conducted, and the experimental results and real-vehicle tests demonstrate significant improvements: steering wheel angle reduction by 10%, enhanced yaw stability (9% higher safety threshold) for the slalom test, and better elk testing performance (>2%). The proposed method offers practical, real-world applicability and provides valuable insights and a reference for yaw control research in the automotive industry.
Liao, YinshengHu, ZhimingCheng, YuanshuLin, RuyaSun, YueGao, SixiaoZhang, Junzhi
This paper presents a novel sensitivity analysis framework for differential braking as a backup steering solution in fail-operational Steer-by-Wire systems. The fault-tolerant design approach of Steer-by-Wire and steering systems for highly automated driving relies on the availability of road wheel actuators (RWA). Redundancies are therefore commonly used to ensure fail-operationality. Since its widespread implementation in production vehicles through electronic stability control, the use of differential braking as a cost-effective measure is desirable to increase functional diversity. However, feasible lateral accelerations through this backup solution are limited compared to conventional steering systems and lie close to ordinary driving scenarios. To address this limitation, this work investigates the influence of chassis parameters on differential braking performance. After defining characteristic values and a simulation test plan, a preliminary analysis using a linear single-track model incorporating differential braking is conducted. The most influential vehicle parameters are identified, including the newly derived effect of rear axle cornering stiffness—an aspect not previously quantified in this context. A second, more detailed sensitivity analysis is performed using a characteristic-based dual-track model equipped with representative brake, steering, and chassis subsystems. Parameter variation ranges are derived from distributed data-based sources. The resulting total effects reveal new insights into the sensitivity of chassis design parameters, including scrub radius, steering friction, rear axle cornering stiffness, and coupling effects of suspension and kinematics. The findings provide valuable guidance for future chassis design in fail-operational steering systems and highlight the importance of underexplored parameters in achieving reliable lateral dynamics through differential braking.
Salzwedel, LeonIatropoulos, JannesHeise, CedricFrohn, ChristianHenze, Roman
This study presents an integrated vehicle dynamics framework combining a 12-degree-of-freedom full vehicle model with advanced control strategies to enhance both ride comfort and handling stability. Unlike simplified models, it incorporates linear and nonlinear tire characteristics to simulate real-world dynamic behavior with higher accuracy. An active roll control system using rear suspension actuators is developed to mitigate excessive body roll and yaw instability during cornering and maneuvers. A co-simulation environment is established by coupling MATLAB/Simulink-based control algorithms with high-fidelity multibody dynamics modeled in ADAMS Car, enabling precise, real-time interaction between control logic and vehicle response. The model is calibrated and validated against data from an instrumented test vehicle, ensuring practical relevance. Simulation results show significant reductions in roll angle, yaw rate deviation, and lateral acceleration, highlighting the effectiveness of the proposed approach. Overall, the framework offers a scalable and robust foundation for developing adaptive stability control systems in modern four-wheeled vehicles
Duraikannu, DineshDumpala, Gangi Reddi
Special vehicles such as off-road vehicles and planetary rovers frequently operate on complex, unpaved road surfaces with varying mechanical parameters. Inaccurate estimation of these parameters can cause subsidence or rollover. Existing methods either lack proactive perception or high precision. This article proposes a fusion framework integrating a visual classifier and a dynamics observer for stable, accurate estimation of road surface parameters. The visual classifier uses an adaptive segmentation system for unpaved roads, leveraging a large-scale vision model and a lightweight network to classify upcoming road surfaces. The dynamics observer employs an online wheel-–ground interaction model using stress approximation, integrating strong tracking theory into an unscented Kalman filter for real-time parameter estimation. The fusion framework performs integration of the classifier and observer outputs at data, feature, and decision levels. An adaptive fading factor and recursive Gaussian process modeling ensure precise estimation of varying parameters. Real-vehicle tests demonstrate that the proposed method reduces the average estimation error by 8.5% and improves convergence speed by 40% during road surface changes, demonstrating potential for integration into off-road vehicle stability control systems.
Zhang, ChenhaoXia, GuangZhang, YangZhou, DayangShi, Qin
As one of the most common types of traffic accidents, tire blowout has become a significant safety issue in the stability control of autonomous vehicles. This paper presents a coordinated control strategy for autonomous vehicles operating under tire blowout conditions. A simplified three-degree-of-freedom vehicle dynamics model and a preview-based kinematic model are developed to capture the complex interactions between lateral and longitudinal motions during a blowout event. Then, the proposed control framework integrates sliding mode control (SMC) with a prescribed-performance function to constrain lateral deviation and heading error within predefined boundaries. To improve emergency path tracking and ensure stability, a transformation-based error bounding method is introduced. Lyapunov-based stability analysis verifies the convergence properties of the closed-loop system. Simulation results validate the effectiveness of the proposed method under both tubeless and tubed tire blowout scenarios. Compared to conventional SMC controllers, the proposed controller reduces lateral error convergence time by up to 58% while ensuring safe stopping within 2.2 seconds after blowout. These results indicate that the controller offers robust and reliable emergency motion control capabilities for autonomous vehicles in extreme tire failure situations.
Xia, HongyangYang, MingLi, HongluoHuang, Yongxian
The rotational resistance coefficient of the bogie is a critical parameter for assessing the operational safety of vehicles, significantly influencing the stability of the vehicle’s snaking motion and the safety of curve negotiation. This paper conducts measurements of the rotational resistance coefficient using a 6- degree-of-freedom bogie test rig, evaluating the variation patterns of the indicator under different vehicle load conditions and air spring inflation states. By establishing a SIMPACK dynamic model of the 6-DOF platform, it is possible to obtain actuator displacement control curves that comply with the EN 14363 standard. Taking a specific subway trailer bogie as an example, the rotational resistance coefficient under various operating conditions was measured. The test results indicate that under the condition of air spring deflation, the rotational resistance coefficient is significantly higher than that under air spring inflation. Moreover, under the condition of air spring deflation, the effect of vehicle load on the rotational resistance coefficient is negligible. Due to assembly errors and the approximate methods used in calculations, the hysteresis curve of the rotational resistance torque-angle measured by the 6-DOF test rig exhibits minor fluctuations, which have a minimal impact on the results, and there is room for further optimization. The method proposed in this paper can provide a basis for vehicle design optimization, reduce the risk of derailment, and also assist in vehicle maintenance and repair during the operation stage to ensure safe operation. It has been widely applied in the design and operation practice of subway vehicles.
Li, LiHu, Jie
This study proposes a novel control strategy for a semi-active truck suspension system using an integral–derivative-tilted (ID-T) controller, developed as a modification of the TID controller. The ant colony optimization (ACO) algorithm is employed to tune the controller parameters. Performance is evaluated on an eight-degrees-of-freedom semi-active suspension system equipped with MR dampers. The objective is to minimize essential dynamic responses (displacement, velocity, and acceleration) of the sprung mass, cabin, and seat. The controller also considers the nonlinear effects including suspension travel, pitch dynamics, dynamic tire loads, and seat-level vibration dose value (VDV). System performance is assessed under both single bump and random road excitations. The ACO-tuned ID-T controller is compared against passive suspension, MR passive (OFF/ON), and ACO-tuned PID and TID controllers. Simulation results demonstrate that the proposed controller achieves superior performance in both time and frequency domains under diverse road conditions.
Gad, S.Metered, H.Bassiuny, A. M.
Trajectory tracking and lateral stability under extreme conditions are critical yet conflicting control objectives due to nonlinear tire dynamics and road adhesion limitation, where accurate characterization of vehicle dynamics for each objective is essential to enable coordinated performance. This article proposes a coordinated control strategy based on switched envelope and composite evaluation to improve both tracking accuracy and stability. Unlike previous stability envelope methods that rely solely on the vehicle’s rear tire saturation boundary to prevent instability, the switched envelope approach incorporates both front and rear tire saturation boundaries to simultaneously mitigate steering loss and instability in trajectory tracking. A critical steering angle, derived from tire slip dynamics and phase plane stability analysis, is formulated as the switching criterion. Additionally, a composite stability evaluation is developed by combining a future disturbance resistance index with the current stability utilization metric, providing a comprehensive measure of vehicle control capability and preventing frequent oscillations among control objectives. Integrated with a switched envelope model predictive control framework, it enables adaptive adjustment of state constraints and control weights to dynamically balance trajectory tracking accuracy and stability. Finally, co-simulations using CarSim and MATLAB/Simulink, along with hardware-in-the-loop experiments, demonstrate the effectiveness of the proposed strategy in enhancing vehicle handling and stability under severe driving scenarios.
Shi, WenboWang, JunlongDing, HaitaoXu, Nan
Automotive Engineering: October 202525AUTP1010/2/2025
Engineering EV, charger safety and security From a quick access port to help firefighters fight EV battery fires faster than otherwise possible to preventing public charger vandalism, here are some developments that haven't made the big headlines. Electronic stability control builds the foundation for safer roads How a mechanically simple idea has kept cars stable for decades, and why it can still evolve for an autonomous future. The factory's hidden power grid Why smart electrical distribution is the new frontier in sustainable manufacturing. Safety by design: a next-gen blueprint for EV batteries The EV industry can - and should - stop pushing decades-old battery architecture well past its limits. Vehicle fire safety with Erbis Biscarri Author turns classroom quest into a tome for anyone who wants to engineer safer cars. Editorial IAA Mobility: A new class of auto show Supplier Eye The new supplier strategy playbook BMW brings EV motor production to Steyr in Austria Ford unveils its universal EV platform Revolutionizing EV battery safety: advanced coatings and composite solutions Inside Slate's Warsaw factory Upstream: better data collection, processing will reduce SDV recalls Sonatus launches AI Director to integrate more AI in more vehicles Simulating forward motion at VI-grade's Zero Prototypes Day Road Ready Hyundai Palisade: A luxury three-row SUV without the price you'd expect Product Briefs Spotlight: EV thermal management, plastics and composites Q&A Factorial CEO: improved cells with 375Wh/kg energy density a 'milestone' for Stellantis
How a mechanically simple idea has kept cars stable for decades, and why it can still evolve for an autonomous future. Since debuting in 1995, Bosch's electronic stability program (ESP) has become one of the most essential safety features in modern vehicles. It's now a standard on nearly every new car sold in America and has been deployed in over 350 million vehicles worldwide. ESP is more than just legacy tech. It's the foundation behind advanced driver assistance, motion control and a more automated future.
Nesbitt, Rich
The article investigates how to detect as quickly as possible whether the driver will lose control of a vehicle, after a disturbance has occurred. Typical disturbances refer to wind gusts, obstacle avoidance, a sudden steer, traversing a pothole, a kick by another vehicle, and so on. The driver may be either human or non-human. Focus will be devoted to human drivers, but the extension to automated or autonomous cars is straightforward. Since the dynamic behavior of vehicle and driver is described by a saddle-type limit cycle, a proper theory is developed to use the limit cycle as a reference trajectory to forecast the loss of control. The Floquet theory has been used to compute a scalar index to forecast stable or unstable motion. The scalar index, named degree of stability (DoS), is computed very early, in the best case, in a few milliseconds after the disturbance has ended. Investigations have been performed at a dynamic driving simulator. A 14 DoF vehicle model, virtually driven by a real human driver, was employed. A number of evasive maneuvers have been examined, both for understeer and oversteer vehicles. The early detection of the loss of control is possible. The sensing of the loss of control could be enhanced with respect to a classical ESP, although a more in-depth investigation is needed. Some issues referring to the robustness of the computation of the DoS are still to be investigated. Nonetheless the DoS seems already applicable for motorsport vehicle and drivers.
Della Rossa, FabioFontana, MatteoGiacintucci, SamueleGobbi, MassimilianoMastinu, GiampieroPreviati, Giorgio
To optimize vehicle chassis handling stability and ride safety, a layered joint control algorithm based on phase plane stability domain is proposed to promote chassis performance under complicated driving conditions. First, combining two degrees-of-freedom vehicle dynamics model considering tire nonlinearity with phase plane theory, a yaw rate and side slip angle phase plane stability domain boundary is drew in real time. Then based on the real-time stability domain and hierarchical control theory, an integrated control system with active front steering (AFS) and direct yaw moment control (DYC) is designed, and the stability of the controller is validated by Lyapunov theory. Finally, the lateral stability of the vehicle is validated by Simulink and CarSim simulations, real car data, and driving simulators under moose test and pylon course slalom test. The experimental results confirm that the algorithm can enhance the maneuverability and ride safety for intelligent vehicles.
Liao, YinshengZhang, ZhijieSu, AilinZhao, BinggenWang, Zhenfeng
This article analyses the fundamental curving mechanics in the context of conditions of perfect steering off-flanging and on-flanging. Then conventional, radial, and asymmetric suspension bogie frame models are presented, and expressions of overall bending stiffness kb and overall shear stiffness ks of each model are derived to formulate the uniform equations of motion on a tangent and circular track. A 4 degree of freedom steady-state curving model is formulated, and performance indices such as stability, curving, and several parameters including angle of attack, tread wear index, and off-flanging performance are investigated for different bogie frame configurations. The compatibility between stability and curving is analyzed concerning those configurations and compared. The critical parameters influencing hunting stability and curving ability are evaluated, and a trade-off between them is analyzed. For the verification, the damped natural frequencies and mean square acceleration response (MSAR) of the mathematical model are analyzed with the same determined from the finite element model and experimental test, respectively. The results determined from mathematical and finite element simulation and experimental tests are found to be similar; therefore, the formulated mathematical model is verified.
Sharma, Rakesh ChandmalSharma, Sunil KumarPalli, SrihariRallabandi, Sivasankara RajuSharma, Neeraj
To address the issue of poor yaw stability in distributed drive electric vehicles under extreme trajectory tracking conditions, this paper proposes a novel control approach that coordinates upper-layer trajectory tracking and stability control with lower-layer active front steering (AFS) and direct yaw moment control (DYC). Firstly, a stability domain boundary is defined in the β−β̇phase plane, and the instability factor is derived based on boundary line characteristics. This factor is used as a weight in the objective function to establish a model predictive control (MPC) for trajectory tracking and handling stability, thereby adjusting the control target weights for both objectives. Secondly, fuzzy logic is used to change the boundary of the phase plane transition field according to the vehicle state to dynamically adjust the intervention timing of the stability control, while AFS and DYC control are used to modify the front wheel steering angle and yaw moment control in the MPC model, and ultimately the torque is distributed to the four wheels. Simulation results show that this control method significantly improves vehicle stability under extreme conditions compared to single-objective MPC, achieving a comprehensive enhancement in trajectory tracking accuracy and vehicle yaw stability performance.
Dou, JingyangWu, JinglaiZhang, Yunqing
The research object of this project is the anti-slip and lateral stability control technique for a distributed three-axis drive vehicle. What differs from the traditional four-motor power system layout is that the third axle has two motors, while the second axle only has one motor. Compared with the traditional design, this layout can reduce dependence on battery performance and maintain motor operation in a high-efficiency range by switching between different operating modes. For example, when driving at high speeds, only the motor on the second axle works, which can improve motor efficiency. When accelerating or climbing, all motors work to provide a large power output. In the research, the vehicle model was first established in Simulink, and then co-simulated with TruckSim. The drive anti-slip control first identified the optimal slip rate for the road, and then used the sliding mode control to determine the driving torque for each wheel, achieving good control effects under various road conditions and driving modes. For example, it improves acceleration performance on muddy roads, bumpy roads, split-traction roads, and so on. The lateral control used a two-layer control strategy: the first layer is sliding mode control, and the second layer is a rule-based distribution layer, which outputs the driving torque for each wheel. Simulations were conducted under double-lane shift and snake test conditions with different adhesion coefficients to verify the effectiveness. The results showed that the control strategy can maintain lateral stability better than traditional systems. The control strategy of the distributed three-axle drive vehicle can achieve better performance than traditional systems.
Shen, RuitengZheng, HongyuKaku, ChuyoZong, Changfu
As a crucial component of highway freight systems, tractor semitrailer vehicles play a key role in the transportation industry. However, their complex vehicle structure can lead to significant lateral instability during emergency obstacle avoidance, posing challenges to the vehicle's dynamic stability and safety. To enhance the emergency obstacle avoidance lateral stability of tractor semitrailer vehicles, a direct yaw moment lateral stability control strategy based on differential driving/braking is proposed. First, a 3-degree-of-freedom ideal linear dynamic model of the tractor-semitrailer is established, and its accuracy is validated. Then, a lateral stability control strategy for emergency obstacle avoidance is proposed. The upper-layer controller employs an improved feedforward differential model-free adaptive control (IMFAC) method to track the target yaw rate and vehicle sideslip angle, while the lower-layer controller focuses on optimizing tire load rate. Additionally, a drive/brake torque distributor is introduced to prioritize regenerative braking. The proposed control strategy is validated under simulated DLC conditions representing emergency obstacle avoidance. The results show that the designed controller improves the lateral stability of the tractor-semitrailer by over 30% in DLC scenarios, ensuring accurate trajectory tracking while maintaining low drive wheel tire load rate. This effectively extends the safety margin for tractor-semitrailer obstacle avoidance and provides valuable insights for improving lateral stability during emergency maneuvers.
Guo, ShaozhongDou, Jingyang
The unicycle self-balancing mobility system offers superior maneuverability and flexibility due to its unique single-wheel grounding feature, which allows it to autonomously perform exploration and delivery tasks in narrow and rough terrains. In this paper, a unicycle self-balancing robot traveling on the lunar terrain is proposed for autonomous exploration on the lunar surface. First, a multi-body dynamics model of the robot is derived based on quasi-Hamilton equations. A three-dimensional terramechancis model is used to describe the interaction between the robot wheels and the lunar soil. To achieve stable control of the robot's attitude, series PID controllers are used for pitch and roll attitude self-balancing control as well as velocity control. The whole robot model and control strategy were built in MATLAB and the robot's traveling stability was analyzed on the lunar terrain.
Shi, JunweiZhang, KaidiDuan, YupengWu, JinglaiZhang, Yunqing
The Distributed Drive Electric Vehicles (DDEVs) offer advantages such as independently controllable driving and braking forces at each wheel, rapid response, and precise control. These features enable effective electronic stability control (ESC) by appropriately distributing torque across each wheel. However, traditional ESC systems typically employ single-wheel hydraulic differential braking, failing to fully utilize the independent torque control capabilities of DDEVs. This study proposes a hierarchical control strategy for distributed driving and braking ESC based on particle filter (PF) and fuzzy integral sliding mode control (FISMC). First, the vehicle state estimation layer uses a three-degree-of-freedom vehicle model and the PF to estimate sideslip angle and vehicle speed. Next, the target torque decision layer includes a target speed tracking controller and a yaw moment decision controller. The yaw moment decision controller uses the FISMC to determine additional yaw moment by comparing the estimated yaw rate and sideslip angle with their ideal values, while dynamically adjusting the sliding mode surface parameters based on vehicle state and driving conditions. Finally, the dynamic torque distribution layer allocates the driving and regenerative braking torques to each wheel according to changes in vertical tire load. A co-simulation platform using MATLAB/Simulink and CarSim is established to validate the proposed control strategy under double lane change and J-turn maneuvers, comparing it with traditional ESC. The results show that the proposed ESC achieves high accuracy in estimating vehicle state and effectively adapts to varying driving conditions while maintaining stable vehicle speed, thereby enhancing driving stability.
Li, XiaolongZheng, HongyuKaku, Chuyo
Vehicle sideslip is a valuable measurement for ground vehicles in both passenger vehicle and racing contexts. At relevant speeds, the total vehicle sideslip, beta, can help drivers and engineers know how close to the limits of yaw stability a vehicle is during the driving maneuver. For production vehicles or racing contexts, this measurement can trigger Electronic Stability Control (ESC). For racing contexts, the method can be used for driver training to compare driver techniques and vehicle cornering performance. In a fleet context with Connected and Autonomous Vehicles (CAVS) any vehicle telemetry reporting large vehicle sideslip can indicate an emergency scenario. Traditionally, sideslip estimation methods involve expensive and complex sensors, often including precise inertial measurement units (IMUs) and dead reckoning, plus complicated sensor fusion techniques. Standard GPS measurements can provide Course Over Ground (COG) with quite high accuracy and, surprisingly, the most challenging measurement is the vehicle orientation. This study presents a low- or moderate-cost method for real-time vehicle sideslip estimation using Real-Time Kinematic (RTK) Global Position System (GPS) receivers. The approach involves a pair of specialized GPS receivers with a moving base and moving rover RTK setup. RTK corrections are provided via an online wireless internet connection. The moving base is positioned at the vehicle's rear axle and the companion rover GPS device is located at the vehicle's center of gravity (CG). This arrangement provides both vehicle orientation and vehicle course over ground at 7Hz. RTK provides direct measurement of both quantities needed to compute vehicle sideslip in real time. The results demonstrate the feasibility of this approach and offers a practical solution for real-world automotive systems. A simple set of driving experiments demonstrate the method’s effectiveness. This approach is a cost-effective solution for sideslip estimation, with applications in ESC, CAVs, driver training and motorsports performance analysis.
Hannah, AndrewCompere, Marc
Path-tracking control occupies a critical role within autonomous driving systems, directly reflecting vehicle motion and impacting both safety and user experience. However, the ever-changing vehicle states, road conditions, and delay characteristics of control systems present new challenges to the path tracking of autonomous vehicles, thereby limiting further enhancements in performance. This article introduces a path-tracking controller, time-varying gain-scheduled path-tracking controller with delay compensation (TGDC), which utilizes a linear parameter-varying system and optimal control theory to account for time-varying vehicle states, road conditions, and steering control system delays. Subsequently, a polytopic-based path-tracking model is applied to design the control law, reducing the computational complexity of TGDC. To evaluate the effectiveness and real-time capability of TGDC, it was tested under a series of complex conditions using a hardware-in-the-loop platform. The results demonstrate that through the polytopic-based path-tracking model and delay compensation strategy in TGDC, it can effectively enhance path-tracking performance with minimal computational load, even under conditions of parameter variability and control delays.
Hu, XuePengZhang, YuHu, YuxuanWang, ZhenfengQin, Yechen
A serious problem of public healthcare around the world is the number of road vehicle accidents, every year almost 1,3 million people die and approximately 20 to 50 million people suffer a non-fatal accident because of a road vehicle accident [1]. As a result of that, in 2021 the World Health Organization stated the “The Second Decade of Action for Road Safety”, which the goal is to prevent at least 50% of deaths and injuries due traffic by 2030. To achieve this goal, the automobile companies have invested in technology and products that can enhance vehicle safety. Despite exist some control systems able to reduce roll, and consequently the roll over, such as active suspension, semi-active suspension, and stability control systems, none of them have as main purpose reduce the number of rollovers. The following study aims to examine the effects of an active anti roll bar, to improve the vehicle dynamics during corners and reduce the risk of a rollover by reducing the roll of the sprung mass and reducing the total weight transfer of the vehicle. The model utilized to reproduce the vehicle dynamics was a bicycle model with 3 degrees of freedom, to describe the tyre lateral forces it was used the nonlinear Pacejka model and as actuator to the active anti roll bar was modeled a direct current motor. The study of cases has shown that during a fishhook maneuver the active anti roll bar was able to improve the performance of the vehicle by reducing the roll angle during the transient and steady state.
Gomes, Pedro CarvalhoTeixeira, Evandro Leonardo SilvaMorais, Marcus Vinicius GirãoFortaleza, Eugenio Liborio FeitoraSantos Gioria, Gustavo
Single lane changing is one of the typical scenarios in vehicle driving. Planning an appropriate lane change trajectory is crucial in autonomous and semi-autonomous vehicle research. Existing polynomial trajectory planning mostly uses cubic or quintic polynomials, neglecting the lateral jerk constraints during lane changes. This study uses seventh-degree polynomials for lane change trajectory planning by considering the vehicle lateral jerk constraints. Simulation results show that the utilization of the seventh-degree method results in a 41% reduction in jerk compared to the fifth-degree polynomial. Furthermore, this study also proposes lane change trajectory schemes that can cater to different driving styles (e.g., safety, efficiency, comfort, and balanced performance). Depending on the driving style, the planned lane change trajectory ensures that the vehicle achieves optimal performance in one or more aspects during the lane change process. For example, with the trajectory that provides the best comprehensive performance under given constraints (initial speed of 20 m/s, lane width of 3.5 m, and a longitudinal distance of 50 m to the obstacle in front), the four-wheel steering model predictive control can effectively track the planned trajectory, with the maximum jerk value being 6.4 m/s3 and the longitudinal speed after lane change being approximately 12.6 m/s. Although this study assumes specific longitudinal displacement before and after the lane change, the methodology is applicable to other scenarios. For example, it can determine the shortest longitudinal displacement and the optimal lane change trajectory given predefined vehicle speeds and maximum lateral acceleration conditions. The lane change trajectories developed in this study can be directly applied to the system design of autonomous vehicles.
Lai, FeiHuang, Chaoqun
Hydro-pneumatic suspension is widely used because of its desirable nonlinear stiffness and damping characteristics. However, the presence of parameter uncertainties and high nonlinearities in the system, lead to unsatisfactory control performance of the traditional controller in practical applications. In response to this challenge, this paper proposes a novel stability control method for active hydro-pneumatic suspension (AHPS). Firstly, a nonlinear mathematical model of the hydro-pneumatic suspension, considering the seal friction, is established based on the hydraulic principle and the knowledge of Fluid dynamics. On the basis of the established hydro-pneumatic suspension nonlinear model, a vehicle dynamics model is established. Secondly, an active disturbance rejection sliding mode controller (ADRSMC) is designed for the vertical, roll, and pitch motions of the sprung mass. The lumped disturbance caused by the model nonlinearities and uncertainties is estimated by the extended state observer (ESO), which is then integrated into the sliding mode control law. This allows the control law to actively adapt to the working state of the suspension system, which can effectively address the impact of uncertainties and nonlinearities on the system. Finally, the simulations are carried out on bump and random roads, two typical working conditions. The results show that the proposed ADRSMC can reduce the amplitude of vehicle acceleration by more than 50% compared to traditional passive hydro-pneumatic suspension, and the optimization effect is better than active disturbance rejection control ADRC). It significantly improves the stability of the vehicle. This study provides a valuable reference for the design of active hydro-pneumatic suspension control strategies.
Niu, ChangshengLiu, XiaoangJia, XingGong, BoXu, Bo
To enhance vehicle dynamic stability during driving, we developed a three-dimensional phase space model that incorporates the sideslip angle of center of mass, yaw rate, and lateral load transfer rate. This model enabled real-time evaluation and active control of vehicle stability. First, longitudinal and lateral controllers were implemented to ensure precise vehicle trajectory. Second, a hierarchical control strategy was designed to actively manage the desired sideslip angle, yaw rate, and roll angle based on the vehicle’s destabilizing conditions, thereby maintaining the vehicle within a stable state space. We simulated and tested the stability analysis methods and integrated control strategies for both cars and trucks under DLC (double lane change) and CDC (circular driving condition) scenarios using joint simulations with CarSim/TruckSim and Simulink. The proposed integrated stability control strategy, which combined MPC-based trajectory tracking with direct yaw moment control and active suspension control, enhanced the vehicle’s directional and roll stability. This approach effectively mitigated vehicle instability under extreme conditions. Compared to the MPC lateral tracking control system, the performance of the integrated control system was significantly improved. In the DLC scenario, the maximum values of the sedan’s lateral deviation, sideslip angle, yaw rate, and vehicle roll angle decreased by 22.6%, 33.9%, 5.5%, and 1.2%, respectively. In the CDC scenario, the truck’s lateral acceleration, sideslip angle, yaw rate, and vehicle roll angle decreased by 7.5%, 46.8%, 8.2%, and 80%, respectively. Additionally, open-loop simulation tests were conducted under fishhook steering conditions for both passenger cars and trucks. The results further validated the effectiveness of the integrated control strategy, demonstrating its ability to significantly improve yaw rate and roll response, thereby enhancing overall vehicle stability under challenging driving conditions.
Lai, FeiXiao, HaoHuang, Chaoqun
In order to reduce the pumping loss of low loads and maximize the lean combustion advantage of hydrogen, the paper proposes a load control strategy based on hydrogen mass, called quality control, for improving thermal efficiency and emissions at low loads. The advantages of quality control and the effect of VVT on the combustion performance of hydrogen internal combustion engines under low loads were discussed. The results show that when the relative air–fuel ratio (λ) increases to more than 2.5, the NOx emissions are reduced to less than 3.5 g/kW · h at the brake mean effective pressure (BMEP) below 8 bar, especially when the BMEP is less than 5 bar, the NOx is within 0.2 g/kW · h. Compared to quantity control based on air mass, the quality control strategy based on hydrogen mass achieves over a 2.0% reduction in pumping loss at BMEP levels lower than 4.4 bar. Furthermore, it enhances thermal efficiency by up to 5% at low loads, while maintaining NOx emissions within 0.2 g/kW · h at BMEP below 5.6 bar. BTE gradually increases with the delay of exhaust valve closing (EVC), decreases first and then increases with the delay of intake valve opening (IVO), and reaches a maximum in early IVO and late EVC areas. In throttle-free hydrogen engines with quality control, VVT technology can be fully utilized to assist stability control in low loads.
Li, YongChen, HongFu, ZhenDu, JiakunWu, Weilong
To address the issues of functional conflicts in execution subsystems and the deterioration of control performance due to model parameter uncertainties in the motion control of distributed vehicle by wire, this article proposes an integrated control strategy considering parameter robustness. This strategy aims to compensate for model mismatch, resolve functional conflicts, and achieve motion coordination. Based on the over-actuation characteristics of distributed vehicle by wire, this article constructs the dynamic model and utilizes the tire cornering properties along with phase portraits to delineate the working regions of the execution subsystems. To deal with model parameter uncertainties and mismatch, tube-based model predictive control (tube-based MPC) is applied to the control strategy design, which compensates for model deviations through state feedback and constructs a robust positively invariant set (RPI) to constrain the system state. Correspondingly, the weights of control inputs are adjusted adaptively, according to the working regions, to optimize the coordination logic of integrated control. In order to verify the effectiveness and feasibility of the strategy, extreme driving condition tests are executed on hardware-in-the-loop (HIL) and real vehicle test platforms. The test results indicate that the strategy proposed in this article is able to reduce the sideslip angle and tracking error of yaw rate, improve driving stability under extreme conditions through integrated control, and especially, it can still maintain precise stability control performance under severe model mismatch, exhibiting strong robustness facing parameter uncertainties.
Chen, GuoyingBi, ChenxiaoZhao, XuanmingYang, LiunanTang, ZhuoYu, Huili
Vehicle path tracking and stability management are critical technologies for intelligent driving. However, their controls are mutually constrained. This article proposes a cooperative control strategy for intelligent vehicle path tracking and stability, based on the stable domain. First, using the vehicle’s two-degrees-of-freedom (DOF) model and the Dugoff tire model, a phase plane representation is constructed for the vehicle’s sideslip angle and sideslip angular velocity. An enhanced method utilizing five eigenvalues is employed to partition the vehicle stability domain. Second, by employing the divided vehicle stable domain, the design of a fuzzy controller utilizes the Takagi–Sugeno (TS) methodology to determine the weight matrix gain for path tracking and stability control. Subsequently, a fuzzy model predictive control (TS-MPC) cooperative control strategy is designed, which takes into account both the precision of path tracking and the stability of the vehicle. Finally, a simulation test and comparative analysis with a generic MPC controller were conducted. The findings indicate that compared to the generic MPC cooperative controller, the control strategy designed in this article markedly enhances the stability of the vehicle and boosts the accuracy of path tracking.
Jiang, ShuhuaiWu, GuangqiangLi, YihangMao, LiboZhang, Dong
In contrast to passenger cars, whose regulation allowed only a simple trailer combination, the autonomous technologies implementation of Electronic Stability Control (ESC) and Advanced Emergency Braking System (AEBS) for commercial vehicles demands more application and calibration efforts. At this case, the focus is on dynamic control of towing vehicles when applying the service brakes of trailer, in special when complex combination as bi-train and road-train, allowed in North and South America. However, the major risk is present occurrence when an ESC or AEBS equipped towing vehicles is connected to a double or triple trailer combination with a conventional braking system, it means: a system that is not equipped with Anti-lock Braking System (ABS). For instance, if during autonomous control, trailers wheels lock, a jackknifing phenomenon can easily occur. Therefore, in case longer and heavier vehicles (LHV) or megatrucks as called in Europe, the strategy for safety assistance systems application should consider trailer configuration maturity level of public reading fleet. In this context, the article aims to propose strategies of implementation and product development that can support the easiest introduction of road safety technologies based on autonomous braking products, in special when it is applied in markets where towed vehicles fleet are greater participation of vehicles equipped with conventional braking system, as occur in Brazil. In order to deliver this, a bibliographic research was carried out looking the available regulation and polities from markets where ESC and AEBS were already implemented, like EU and US. In addition, it was studied an Argentine government program that introduce at same time: road safety technologies, technological fleet renewal policies, periodic vehicle inspection, however offsetting the increased costs with logistical benefits for transport business.
Guarenghi, Vinicius MendesPizzi, Rafael FortunaDepetris, AlessandroPinto, Gustavo Laranjeira NunesCollobialli, Germano
With the modernization of agriculture, the application of unmanned agricultural special vehicles is becoming increasingly widespread, which helps to improve agricultural production efficiency and reduce labor. Vehicle path-tracking control is an important link in achieving intelligent driving of vehicles. This paper designs a controller that combines path tracking with vehicle lateral stability for four-wheel steer/drive agricultural special electric vehicles. First, based on a simplified three-degrees-of-freedom vehicle dynamics model, a model predictive control (MPC) controller is used to calculate the front and rear axle angles. Then, according to the Ackermann steering principle, the four-wheel independent angles are calculated using the front and rear axle angles to achieve tracking of the target trajectory. For vehicle lateral stability, the sliding mode control (SMC) is used to calculate the required direct yaw moment control (DYC) of the vehicle, and wheel torque distribution is carried out considering the front and rear axle loads and road adhesion coefficient. CarSim and MATLAB/Simulink were chosen to build a joint simulation platform, and simulation experiments were conducted under two working conditions: high adhesion road surface and low adhesion road surface. The simulation results showed that the controller designed in this paper can improve the lateral stability of the vehicle while ensuring good path-tracking accuracy.
Huang, BinYang, NuorongMa, LiutaoWei, Lexia
Vehicle yaw stability control (YSC) can actively adjust the working state of the chassis actuator to generate a certain additional yaw moment for the vehicle, which effectively helps the vehicle maintain good driving quality under strong transient conditions such as high-speed turning and continuous lane change. However, the traditional YSC pursues too much driving stability after activation, ignoring the difference of multi-objective requirements of yaw maneuverability, actuator energy consumption and other requirements in different vehicle stability states, resulting in the decline of vehicle driving quality. Therefore, a vehicle yaw stability model predictive control strategy for dynamic and multi-objective requirements is proposed in this paper. Firstly, the unstable characteristics of vehicle motion are analyzed, and the nonlinear two-degree-of-freedom vehicle dynamics models are established respectively. Secondly, the vehicle yaw stability control strategy is designed: The two-line method is used to extract the boundary of β−β̇ phase portrait. On this basis, the geometric distance quantization method is applied to establish the dynamic mapping relationship between the multi-objective requirements of driving stability, yaw maneuverability, actuator energy consumption and the weight of YSC cost function in different vehicle stability states. The model predictive theory and rule-based single wheel differential braking technology are applied to achieve vehicle stability control. Finally, a joint simulation platform is built based on vehicle dynamics simulation software CarSim and MATLAB/Simulink for testing and verification. The simulation results show that the YSC designed in this paper can adaptively adjust the controller output according to the dynamic multi-objective requirements in different vehicle stability states, and effectively improve the driving quality of the vehicle under strong transient conditions.
Wang, HanlinWu, JianChen, ZhichengHe, RuiLi, Haiqiao
In order to improve the trajectory tracking accuracy and yaw stability of vehicles under extreme conditions such as high speed and low adhesion, a coordinated control method of trajectory tracking and yaw stability is proposed based on four-wheel-independent-driving vehicles with four-wheel-steering. The hierarchical structure includes the trajectory tracking control layer, the lateral stability control decision layer, and the four-wheel angle and torque distribution layer. Firstly, the upper layer establishes a three-degree-of-freedom vehicle dynamics model as the controller prediction model, the front wheel steering controller is designed to realize the lateral path tracking based on adaptive model predictive control algorithm and the longitudinal speed controller is designed to realize the longitudinal speed tracking based on PID control algorithm. Then, the middle layer decides the rear wheel steering angle and the additional yaw moment to maintain the vehicle's yaw stability based on the super-twisting sliding mode control algorithm and the improved particle swarm PID (IPSO-PID) control algorithm, respectively. Next, the lower layer allocates the four wheel steering angle according to the Ackermann Angle relation of four-wheel-steering vehicle, and optimally assigns the four wheel hub motor torques using sequential least squares planning with the objective function of minimizing the sum of the four tires' adhesion utilization. Finally, the CarSim/Simulink co-simulation platform is built to carry out the simulation test of medium-speed low-adhesion and high-speed high-adhesion double-lane-change conditions respectively. The simulation results show that the coordinated control strategy of trajectory tracking and yaw stability designed in this paper can improve the path tracking accuracy of the vehicle and meet the yaw stability of the vehicle under dangerous working conditions.
Fu, YaoXie, RenminKaku, ChuyoZheng, Hongyu
Heavy commercial vehicles have large variations in load and high centroid positions, so it is particularly important to obtain timely and accurate load information during driving. If the load information can be accurately obtained and the braking force of each axle can be distributed on this basis, the braking performance and safety of the entire vehicle can be improved. Heavy commercial vehicle load information is different from passenger vehicles, so it is particularly important to study commercial vehicles engaged in freight and passenger transportation. Presently, numerous research endeavors focus on evaluating the quality of passenger vehicles. However, heavy commercial vehicles exhibit notable distinctions compared to their passenger counterparts. Due to substantial variations in vehicle mass pre and post-loading, coupled with notable suspension deformations, significant changes are observed. Hence, the task of estimating the mass of heavy commercial vehicles proves considerably more intricate than that of passenger vehicles. Nevertheless, the process of mass estimation is intricately linked to vehicular safety. Therefore, delving into the mass estimation of heavy commercial vehicles holds paramount significance in the realm of safety. The demand for precise access to commercial vehicle information is notably heightened in the context of intelligent technology. The Hill Start Assist system necessitates the real-time computation of engine torque, contingent upon the vehicle mass and road gradient, with the objective of minimizing fuel injection during hill starts. In the context of an electronic parking brake system, the determination of ground braking force entails acquiring the mass of the vehicle. The more accurate the mass, the better the braking control effect. In the electronic stability control system for vehicle bodies, the stability factor is affected by the quality of the entire vehicle, and its reliability will affect the judgment of oversteer and understeer. Vehicle quality and road slope are also key parameters for making gear decisions in gear shifting control, and accurate estimation of them can improve the quality of gear shifting control. Therefore, when conducting intelligent vehicle control, it is necessary to obtain real-time vehicle mass and road slope information during vehicle driving. In this paper, a multi forgetting factor recursive least square method is used to identify the vehicle mass and road slope for the problem of inconsistency between the vehicle mass and road slope variation frequency of heavy commercial vehicles. Firstly, a dynamic system model considering the rotational inertia of heavy commercial vehicles is established. Secondly, a multi forgetting factor recursive least square algorithm for vehicle mass and road slope identification is designed. Finally, the identification algorithm is verified at half load and full load respectively.
Zheng, HongyuXin, YafeiYan, Yang
This paper presents a torque distribution strategy for four-wheel independent drive electric vehicles (4WIDEVs) to achieve both handling stability and energy efficiency. The strategy is based on the dynamic adjustment of two optimization objectives. Firstly, a 2DOF vehicle model is employed to define the stability control objective for Direct Yaw moment Control (DYC). The upper-layer controller, designed using Linear Quadratic Regulator (LQR), is responsible for tracking the target yaw rate and target sideslip angle. Secondly, the lower-layer torque distribution strategy is established by optimizing the tire load rate and motor energy consumption for dynamic adjustment. To regulate the weights of the optimization targets, stability and energy efficiency allocation coefficient is introduced. Simulation results of double lane change and split μ road conditions are used to demonstrate the effectiveness of the proposed DYC controller.
Dou, JingyangChen, ZixuanZhang, YunqingWu, Jinglai
Reference velocity (i.e. the absolute velocity of vehicle center of gravity) is a key parameter for vehicle stability control functions as well as for the powertrain control functions of hybrid electric vehicle (HEV). Most reference velocity estimation methods employ the vehicle kinematic and tire dynamic equations to construct high order linear or nonlinear model with a set of parameters and sensor measurements. When using those models, delicate algorithm should be designed to prevent the estimates from deviating along with the increase of nonlinearity, modeling error and noise that introduced by high order, parameter approximation, and sensor measurements, respectively. Alternatively, to improve the function robustness and calibration convenience, a straightforward online estimation method is developed in the paper by using a second-order powertrain dynamic model that only need a small set of vehicle parameters and sensor values. First, the HEV powertrain dynamic model is established for the vehicle longitudinal velocity estimation. Second, a classic Luenberger observer with variable estimation gains are designed. Third, the variable estimation gains are scheduled based on the vehicular operational conditions to determine whether the estimates need to be dominated by the dynamic model or by the measurements in different condition. Then the algorithm is integrated into the vehicle control unit (VCU) of a mass production HEV, which is a powertrain supervisory controller that possesses all the control inputs and measurements signals needed by the observer. Finally, the estimation accuracy is verified by experiments on both high- and low-μ (-adhesion) road, such as the snow surface, ice surface, and urban concrete pavement, etc. Due to the low order and minor parameters and measurements needed, as well as the variable estimation gain scheduled with operational conditions, the algorithm robustness and calibration convenience are guaranteed.
Li, HuanLiu, XuewuWang, JinhangChen, LihuaXu, YinWu, Meng
Vehicle dynamic control could improve vehicle performance. Vehicle stability is vital to the determination of vehicle dynamic control strategy. The phase plane method is one of the most common methods to judge vehicle stability. To determine the 4WS (four-wheel steering) vehicle stability status faster and more accurately, a novel method to assess the vehicle stability is based on the vehicle sideslip angle and angular velocity ( β-β˙) phase plane. At first, the 2 DOF (degree of freedom) model with a nonlinear tire model is established to acquire β-β˙ phase plane. Then the boundary of the stability region generated by the current method is compared. A crosspoint-ellipse method is provided based on the boundary comparison with the ideal boundary. The boundary function determined by the crosspoint-ellipse method is fitted based on vehicle dynamic theory and the boundary analysis with different steering angles, velocity, and road adhesion coefficient. At last, the transition area between the stable and unstable region is acquired by considering the uncertainty of the road adhesion coefficient. The provided method could describe the stable boundary closer to the ideal region with a relatively simple function, which could lay a good foundation for vehicle dynamic control.
Peng, DengzhiXia, ZuguoWang, LongLiu, Qing
Outrigger is mounted on the test vehicle during handling test maneuvers, such as double lane change, constant radius cornering, J-turn, etc. The aim of these outriggers is to protect the driver & vehicle from rollover during testing of vehicle electronic stability control systems under various dynamic maneuvers as per AIS 133. Outrigger design has to be achieved within a certain mass and roll moment of inertia as per AIS 133 guidelines. The paper discusses design which includes load path analysis, material comparison to maximize strength per unit weight, shape, dimensional finalization, etc. Torsion is generated when the skidpad comes in contact with the ground which we have tried to balance in the free body diagram (FBD) by changing the skidpad contact point for reducing the stress. Finite element analysis is done on the design developed after setting boundary conditions arrived from FBD. The developed design is then manufactured and successfully implemented in the testing of vehicles as per AIS-133.
Rathore, Gopal SinghChawla, Shubham
In the commercial vehicle business, vehicle availability is a pivotal factor for the profitability of the customer. Nonetheless, the intricate nature of the technologies embedded in modern day engines and exhaust after-treatment systems coupled with the variability of the duty cycles of end applications of the vehicles imposes added challenges on the vehicle's sustained performance and reliability. In this context, the ability to predict potential failures through tools like telematics and real-time data analytics presents a significant opportunity for original equipment manufacturers (OEMs) to deliver distinctive value to their customers. A modern-day commercial vehicle has a minimum of 5 micro controllers managing the performance and performing the on-board diagnostics of various sub-systems like engine, after treatment system, transmission, Cab and stability controls, the driver interface, and advisory systems etc., They operate independently and also sync with each other as master and slave relationship to perform various tasks. Forecasting failures of critical systems like engine, after treatment system etc., in advance to prevent a major vehicle breakdown is a challenging task. But data available from the on-board micro controllers like the engine and after-treatment (AT) controller transmitted via telematics provides an opportunity to assess the health of these systems on real time basis. Through data analytics using the empirical models developed based on historical test data it is possible to predict the likelihood of failure and prescribe preventive measures. This paper presents an application using such Modelled data analytics to analyze the live parameter data and apply predefined logics to predict engine and after treatment system health and possible occurrence of a failure. Application using PYTHON was developed to evaluate the severity of application duty cycle on engine and evaluate the health of major engine and AT sub-systems. The logic and modelling were verified on field vehicle data and the application was able to predict the failure accurately. These models were then integrated in the iALERT platform which is the Telematics solution offered by Ashok Leyland to its customer. This enables the fleet owners to gauge the criticality of the duty-cycle to which their fleet are subjected to and take necessary preventive actions. Moving forward, the predictions will be enhanced with more field data and with integration of AI tools to improve the accuracy of prediction.
K.S, Guru PrasannaD.V, RamkumarS, KannanJ, Narayana ReddyK.R, KarthikeyanD., SomsekarM.D, SenthilkumarN, Augustin SelvakumarS.P, Suprabhan
To address the challenge of directly measuring essential dynamic parameters of vehicles, this article introduces a multi-source information fusion estimation method. Using the intelligent front camera (IFC) sensor to analyze lane line polynomial information and a kinematic model, the vehicle’s lateral velocity and sideslip angle can be determined without extra sensor expenses. After evaluating the strengths and weaknesses of the two aforementioned lateral velocity estimation techniques, a fusion estimation approach for lateral velocity is proposed. This approach extracts the vehicle’s lateral dynamic characteristics to calculate the fusion allocation coefficient. Subsequently, the outcomes from the two lateral velocity estimation techniques are merged, ensuring rapid convergence under steady-state conditions and precise tracking in dynamic scenarios. In addition, we introduce a tire parameter online adaptive module (TPOAM) to continually update essential tire parameters such as cornering stiffnesses, with its effectiveness demonstrated through DLC and slalom simulation tests. Using a dual extended Kalman filter (DEKF) observer, the article allows for joint estimation of vehicle states and tire parameters. Ultimately, we offer a cost-effective estimation method of vital dynamic vehicle parameters to support the motion control module in autonomous driving.
Chen, GuoyingYao, JunGao, ZhenhaiGao, ZhengWang, XinyuXu, NanHua , Min
Direct debugging of a vertical takeoff and landing (VTOL) fixed-wing aircraft’s control system can easily result in risk and personnel damage. It is effectively to employ simulation and numerical methods to validate control performance. In this paper, the attitude stabilization controller for VTOL fixed-wing aircraft is designed, and the controller performance is verified by MATLAB and visual simulation software, which significantly increases designed efficiency and safety of the controller. In detail, we first develop the VTOL fixed-wing aircraft’s six degrees of freedom kinematics and dynamics models using Simulink module, and the cascade PID control technique is applied to the VTOL aircraft’s attitude stabilization control. Then the visual simulation program records the flight data and displays the flight course and condition, which can validate the designed controller performance effectively. It can be concluded that the designed VTOL fixed-wing aircraft control visual simulation system, can demonstrate the effectiveness of the control algorithm, which has a wide range of potential applications.
Li, WeiShi, JiekaiWang, FangBai, Jie
For intelligent vehicles, a fast and accurate estimation of road slope is of great significance for many aspects, including the steering comfort, fuel economy, vehicle stability control, driving decision-making, etc. But the commonly used estimation methods nowadays usually demand additional sensors or complex dynamic models, causing increase in system complexity as well as decrease in accuracy. To solve these problems, this paper puts forward a real-time road slope estimation algorithm leveraging the relationship between pitch angle and road slope, which only requires low sensors cost and computational complexity. Firstly, a GNSS/INS fusion system is established to obtain the pitch angle with respect to the navigation frame, which couples the vehicle’s pitch angle in vehicle frame and road slope angle. Then, based on the different characteristics in frequency domain of the two components, frequency domain analysis is conducted and low-pass filter is used to separate out road slope signal. Besides, considering the slope change during driving, a parameter adaption strategy is designed in order to timely track changes of slope conditions. Experimental results show that the proposed method has a good real-time performance and the average error is below 0.3 deg even when the road slope changes rapidly.
Chen, MengyuanXiong, LuGao, Letian
For distributed drive electric vehicles (DDEV) equipped with an electronic hydraulic braking system (EHB) and four-wheel hub motors, when one or more hub motors have regenerative braking failure, because the braking torque of the four wheels is inconsistent, additional yaw moment will be formed on the vehicle, resulting in the loss of directional stability of the vehicle during braking. If it occurs at high speeds, it will further threaten driving safety. To solve the above problems, a new hierarchical control architecture is established in this paper. Firstly, taking DDEV as the research object, the vehicle dynamics model and EHB braking system model are built. Then, a state observer based on an adaptive Kalman filter is designed in the upper layer to estimate the vehicle’s sideslip angle and yaw rate in real time. In the judgment decision-making layer, the phase plane is used to divide the stability domain boundary of the vehicle, and the quasi-stability tolerance band judges the vehicle’s driving state. Secondly, the lower stability controller is constructed based on the sliding mode control theory. EHB can flexibly distribute hydraulic braking force to compensate for the vehicle’s braking force, offset the additional yaw moment, and maintain the straight line of the vehicle. Finally, experimental verification is carried out in Matlab/ CarSim and hardware-in-the-loop (HIL) platforms. The results show that the proposed method can effectively predict the state and closed-loop stability control of DDEV, and reduce the deviation distance caused by regenerative braking failure, effectively ensuring the vehicle in the event of regenerative braking failure driving safety.
Fang, TingZhao, LinfengHu, JinfangMei, ZhenWang, MuyunSun, Bin
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