Real-time Tire Parameters Observer for Vehicle Dynamics Stability Control

The performance of the vehicle dynamics stability control system（DSC） is dominated by the accurate estimation of tire forces in real-time.The characteristics of tire forces are determined by tire dynamic states and parameters,which vary in an obviously large scope along with different working conditions.Currently,there have been many methods based on the nonlinear observer to estimate the tire force and dynamic parameters,but they were only used in off-line analysis because of the computation complexity and the dynamics differences of four tires in the steering maneuver conditions were not considered properly.This paper develops a novel algorithm to observe tire parameters in real-time controller for DSC.The algorithm is based on the sensor-fusion technology with the signals of DSC sensors,and the tire parameters are estimated during a set of maneuver courses.The calibrated tire parameters in the control cycle are treated as the elementary states for vehicle dynamics observation,in which the errors between the calculated and the measured vehicle dynamics are used as the correcting factors for the tire parameter observing process.The test process with a given acceleration following a straight line is used to validate the estimation method of the longitudinal stiffness;while the test process with a given steering angle is used to validate the estimated value of the cornering stiffness.The ground test result shows that the proposed algorithm can estimate the tire stiffness accurately with an acceptable computation cost for real-time controller only using DSC sensor signal.The proposed algorithm can be an efficient algorithm for estimating the tire dynamic parameters in vehicle dynamics stability control system,and can be used to improve the robustness of the DSC controller.

Map-based control method for vehicle stability enhancement

This work proposes a map-based control method to improve a vehicle's lateral stability, and the performance of the proposed method is compared with that of the conventional model-referenced control method. Model-referenced control uses the sliding mode method to determine the compensated yaw moment; in contrast, the proposed map-based control uses the compensated yaw moment map acquired by vehicle stability analysis. The vehicle stability region is calculated by a topological method based on the trajectory reversal method. A 2-DOF vehicle model and Pacejka's tire model are used to evaluate the proposed map-based control method. The properties of model-referenced control and map-based control are compared under various road conditions and driving inputs. Model-referenced control uses a control input to satisfy the linear reference model, and it generates unnecessary tire lateral forces that may lead to worse performance than an uncontrolled vehicle with step steering input on a road with a low friction coefficient. However, map-based control determines a compensated yaw moment to maintain the vehicle within the stability region,so the typical responses of vehicle enable to converge rapidly. The simulation results with sine and step steering show that map-based control provides better the tracking responsibility and control performance than model-referenced control.

MULTI-AXLE VEHICLE STABILITY BASED ON WHOLE VEHICLE MODEL

From the analysis of experiment data of the multi-axle vehicle chassis searching process, it is less accurate to predict multi-axle vehicle dynamic characteristic with simplified two-axle vehicle model. So it is important to find out a more effective modeling method in the study of multi-vehicle stability. In the development of heat transfer fluid（HTF） six-axle vehicle, a whole vehicle multi-body dynamic model is built through collaborate flowchart using Teamcenter Engineering, UG NX3 and MSC.Adams. The modeling method of connected hydragas spring suspension is validated by running test results. Based on this whole vehicle model, a kinematical analysis of suspension is implemented to achieve optimized suspension geometry parameters according to the stable requirement. Then, different handling simulations are carried out with regard to various tire characteristics, driving con- figurations, and equipments. According to the evaluation of whole vehicle handling characteristic, some design rules are summarized to improve the stability of multi-axle vehicle.

Control allocation algorithm for over-actuated electric vehicles

A control allocation algorithm based on pseudo-inverse method was proposed for the over-actuated system of four in-wheel motors independently driving and four-wheel steering-by-wire electric vehicles in order to improve the vehicle stability. The control algorithm was developed using a two-degree-of-freedom(DOF) vehicle model. A pseudo control vector was calculated by a sliding mode controller to minimize the difference between the desired and actual vehicle motions. A pseudo-inverse controller then allocated the control inputs which included driving torques and steering angles of the four wheels according to the pseudo control vector. If one or more actuators were saturated or in a failure state, the control inputs are re-allocated by the algorithm. The algorithm was evaluated in Matlab/Simulink by using an 8-DOF nonlinear vehicle model. Simulations of sinusoidal input maneuver and double lane change maneuver were executed and the results were compared with those for a sliding mode control. The simulation results show that the vehicle controlled by the control allocation algorithm has better stability and trajectory-tracking performance than the vehicle controlled by the sliding mode control. The vehicle controlled by the control allocation algorithm still has good handling and stability when one or more actuators are saturated or in a failure situation.

Research on Direct Yaw Moment Control Strategy of Distributed-Drive Electric Vehicle Based on Joint Observer

Combined with the characteristics of the distributed-drive electric vehicle and direct yaw moment control,a double-layer structure direct yaw moment controller is designed.The upper additional yaw moment controller is constructed based on model predictive control.Aiming at minimizing the utilization rate of tire adhesion and constrained by the working characteristics of motor system and brake system,a quadratic programming active set was designed to optimize the distribution of additional yaw moments.The road surface adhesion coefficient has a great impact on the reliability of direct yaw moment control,for which joint observer of vehicle state parameters and road surface parameters is designed by using unscented Kalman filter algorithm,which correlates vehicle state observer and road surface parameter observer to form closed-loop feedback correction.The results show that compared to the“feedforward+feedback”control,the vehicle’s error of yaw rate and sideslip angle by the model predictive control is smaller,which can improve the vehicle stability effectively.In addition,according to the results of the docking road simulation test,the joint observer of vehicle state and road surface parameters can improve the adaptability of the vehicle stability controller to the road conditions with variable adhesion coefficients.

Vehicle path tracking by integrated chassis control

The control problem of trajectory based path following for passenger vehicles is studied. Comprehensive nonlinear vehicle model is utilized for simulation vehicle response during various maneuvers in MATLAB/Simulink. In order to follow desired path, a driver model is developed to enhance closed loop driver/vehicle model. Then, linear quadratic regulator(LQR) controller is developed which regulates direct yaw moment and corrective steering angle on wheels. Particle swam optimization(PSO) method is utilized to optimize the LQR controller for various dynamic conditions. Simulation results indicate that, over various maneuvers, side slip angle and lateral acceleration can be reduced by 10% and 15%, respectively, which sustain the vehicle stable. Also, anti-lock brake system is designed for longitudinal dynamics of vehicle to achieve desired slip during braking and accelerating. Proposed comprehensive controller demonstrates that vehicle steerability can increase by about 15% during severe braking by preventing wheel from locking and reducing stopping distance.

Stabilization of coordinated motion for underwater vehicles

This paper presents a coordinating and stabilizing control law for a group of underwater vehicles with unstable dynamics. The coordinating law is derived from a potential that only depends on the relative configuration of the underwater vehicles. Being coordinated,the group behaves like one mechanical system with symmetry,and we focus on stabilizing a family of coordinated motions,called relative equilibria. The stabilizing law is derived using energy shaping to stabilize the relative equilibria which involve each vehicle translating along its longest（unstable） axis without spinning,while maintaining a relative configuration within the group. The proposed control law is physically motivated and avoids the linearization or cancellation of nonlinearities.

Characteristics Extraction of Vehicle State Information Based on Entropy Calculation

A method of extracting and detecting vehicle stability state characteristics based on entropy is proposed.The vehicle’s longitudinal and lateral dynamics models are established for complex driving and maneuver conditions.The corresponding state observer is designed by adopting the moving horizon estimation algorithm,which realizes the observation of the vehicle stability state considering the global state information.Meanwhile,the Shannon entropy is modified to approximate entropy,and the approximate entropy value of the observed vehicle state is calculated.Furthermore,the optimal controller is designed to further validate the reliability of the entropy value as the reference of control system.Simulation results demonstrate that this method can quickly detect the instability state of the system during the process of vehicle driving,which provides a reference for risk prediction and active control.

Analysis of the Material Properties of Vehicle Suspension Coil Spring

The suspension coil spring is one of the most important components in a vehicle suspension system. Its primary function is to absorb the vibrational shocks that are occasioned by irregular road surface to provide the vehicle with stability and ride comfort. The main objective of this study is to design a suspension coil spring made of structural steel for light duty vehicles with the aim of weight and cost reduction. This study was motivated by the government of Ghana’s actions to industrialise the automotive sector of the country through government policies and programs. The study made use of high carbon steel and low carbon steel as the control materials and structural steel as the implementing material. This was done to determine the suitability of structural steel for vehicle suspension coil spring. The study analysed parameters such as total deformation, equivalent Von Mises stress, maximum shear stress, and safety factor in the static structural analysis. The fatigue analysis also analysed parameters such as fatigue life and fatigue alternating stress. The results of the study revealed that the suspension spring made of structural steel has superior properties against all the parameters set for this study apart from deformation. The two control materials that are known for suspension coil spring design and manufacture have better properties to withstand deformation than the implementing material.

Real-Time nonlinear predictive controller design for drive-by-wire vehicle lateral stability with dynamic boundary conditions

Due to flexible drive-by-wire technology,vehicle stability control can improve handling and lateral stability under extreme conditions.However,this technology can also increase the probability of random transmission delay.This paper proposes a nonlinear model predictive control(NMPC)strategy to improve vehicle stability and compensate for the random time delay.First,by combining the nonlinear dynamic characteristics and driver behavior,we obtain a stable region of the yaw rate and the sideslip angle under complex driving conditions.Second,an NMPC controller is designed to track the reference values in the identified stable region to improve the handling and lateral stability.Finally,the actuator receives the optimized control sequence and compensates for the random time delay of the transmission channel.CarSim/Simulink simulation and hardware-in-the-loop experiment results show that the proposed controller with dynamic boundary conditions can better track the expected value of the yaw rate and suppress the sideslip angle under low adhesion road conditions.

Stability Analysis of Two-Point Mooring Autonomous Underwater Vehicle

Static stability analysis of the two-point mooring autonomous underwater vehicle(AUV) is presented.The mathematic model is a set of equilibrium equations describing the attitude of the AUV.The mooring lines are regarded as inelastic catenaries,and five degrees of freedom of AUV are considered.The stability of the system is represented by inequality conditions between several physical quantities and the corresponding limitations.We analyze stability of the prime AUV and find that the AUV has a flow-following tendency,which makes the swing angle big.The result shows that the two-point mooring AUV can remain stable under 2.5 kn ocean current speed,and it will weigh anchor when the speed is greater than 3 kn.Subsequent parametric study reveals the influence of the designing parameters on the stability.

Can software-defined vehicles never roll over:A perspective of active structural transformation

The revolution of physical structure is highly significant for future software defined vehicles(SDV).Active structural transformation is a promising feature of the next generation of vehicle physical structure.It can enhance the dynamic performance of vehicles,thus providing safer and more comfortable ride experiences,such as the ability to avoid rollover in critical situations.Based on the active structural transformation technology,this study proposes a novel approach to improve the dynamic performance of a vehicle.The first analytical motion model of a vehicle with active structural transformation capability is established.Then,a multi-objective optimization problem with the adjustable parameters as design variables is abstracted and solved with an innovative scenario specific optimization method.Simulation results under different driving scenarios revealed that the active transformable vehicle applying the proposed method could significantly improve the handling stability without sacrificing the ride comfort,compared with a conventional vehicle with a fixed structure.The proposed method pipeline is defined by the software and supported by the hardware.It fully embodies the characteristics of SDV,and inspires the improvement of multiple types of vehicle performance based on the concept of“being defined by software”and the revolution of the physical structure.

Real‑Time Predictive Control of Path Following to Stabilize Autonomous Electric Vehicles Under Extreme Drive Conditions

A novel real-time predictive control strategy is proposed for path following(PF)and vehicle stability of autonomous electric vehicles under extreme drive conditions.The investigated vehicle configuration is a distributed drive electric vehicle,which allows to independently control the torques of each in-wheel motor(IWM)for superior stability,but bringing control com-plexities.The control-oriented model is established by the Magic Formula tire function and the single-track vehicle model.For PF and direct yaw moment control,the nonlinear model predictive control(NMPC)strategy is developed to minimize PF tracking error and stabilize vehicle,outputting front tires’lateral force and external yaw moment.To mitigate the calcu-lation burdens,the continuation/general minimal residual algorithm is proposed for real-time optimization in NMPC.The relaxation function method is adopted to handle the inequality constraints.To prevent vehicle instability and improve steering capacity,the lateral velocity differential of the vehicle is considered in phase plane analysis,and the novel stable bounds of lateral forces are developed and online applied in the proposed NMPC controller.Additionally,the Lyapunov-based constraint is proposed to guarantee the closed-loop stability for the PF issue,and sufficient conditions regarding recursive feasibility and closed-loop stability are provided analytically.The target lateral force is transformed as front steering angle command by the inversive tire model,and the external yaw moment and total traction torque are distributed as the torque commands of IWMs by optimization.The validations prove the effectiveness of the proposed strategy in improved steering capacity,desirable PF effects,vehicle stabilization,and real-time applicability.

Aeroservoelastic modeling and analysis of a canard-configured air-breathing hypersonic vehicles

Air-breathing hypersonic vehicles （HSVs） are typically characterized by interactions of elasticity, propulsion and rigid-body flight dynamics, which may result in intractable aeroservoelastic problem. When canard is added, this problem would be even intensified by the introduction of low-frequency canard pivot mode. This paper concerns how the aeroservoelastic stability of a canard-configured HSV is affected by the pivot stiffnesses of all-moveable horizontal tail （HT） and canard. A wing/pivot system model is developed by considering the pivot torsional flexibility, fuselage vibration, and control input. The governing equations of the aeroservoelastic system are established by combining the equations of rigid-body motion, elastic fuselage model, wing/pivot system models and actuator dynamics. An unsteady aerodynamic model is developed by steady Shock-Expansion theory with an unsteady correction using local piston theory. A baseline controller is given to provide approximate inflight characteristics of rigid-body modes. The vehicle is trimmed for equilibrium state, around which the linearized equations are derived for stability analysis. A comparative study of damping ratios, closed-loop poles and responses are conducted with varying controller gains and pivot stiffnesses. Available bandwidth for control design is discussed and feasible region for pivot stiffnesses of HT and canard is given.

Active steering control strategy for articulated vehicles

To improve maneuverability and stability of articulated vehicles, we design an active steering controller, including tractor and trailer controllers, based on linear quadratic regulator(LQR) theory. First, a three-degree-of-freedom(3-DOF) model of the tractor-trailer with steered trailer axles is built. The simulated annealing particle swarm optimization(SAPSO) algorithm is applied to identify the key parameters of the model under specified vehicle speed and steering wheel angle. Thus, the key parameters of the simplified model can be obtained according to the vehicle conditions using an online look-up table and interpolation. Simulation results show that vehicle parameter outputs of the simplified model and Truck Sim agree well, thus providing the ideal reference yaw rate for the controller. Then the active steering controller of the tractor and trailer based on LQR is designed to follow the desired yaw rate and minimize their side-slip angle of the center of gravity(CG) at the same time. Finally, simulation tests at both low speed and high speed are conducted based on the Truck Sim-Simulink program. The results show significant effects on the active steering controller on improving maneuverability at low speed and lateral stability at high speed for the articulated vehicle. The control strategy is applicable for steering not only along gentle curves but also along sharp curves.

Distributed receding horizon control for fuel-efficient and safe vehicle platooning

This paper investigates the problem of fuel-efficient and safe control of autonomous vehicle platoons. We present a two-part hierarchical control method that can guarantee platoon stability with minimal fuel consumption. The first part vehicle controller is derived in the context of receding horizon optimal control by constructing and solving an optimization problem of overall fuel consumption. The Second part platoon controller is a complementation of the first part, which is given on the basis of platoon stability analysis. The effectiveness of the presented platoon control method is demonstrated by both numerical simulations and experiments with laboratory-scale Arduino cars.

Approach and landing guidance design for reusable launch vehicle using multiple sliding surfaces technique

An autonomous approach and landing（A＆L） guidance law is presented in this paper for landing an unpowered reusable launch vehicle（RLV） at the designated runway touchdown. Considering the full nonlinear point-mass dynamics, a guidance scheme is developed in threedimensional space. In order to guarantee a successful A＆L movement, the multiple sliding surfaces guidance（MSSG） technique is applied to derive the closed-loop guidance law, which stems from higher order sliding mode control theory and has advantage in the finite time reaching property.The global stability of the proposed guidance approach is proved by the Lyapunov-based method.The designed guidance law can generate new trajectories on-line without any specific requirement on off-line analysis except for the information on the boundary conditions of the A＆L phase and instantaneous states of the RLV. Therefore, the designed guidance law is flexible enough to target different touchdown points on the runway and is capable of dealing with large initial condition errors resulted from the previous flight phase. Finally, simulation results show the effectiveness of the proposed guidance law in different scenarios.