Development and Validation of a Scaled Electric Combat Vehicle Tire Model

Pneumatic tire modeling and validation have been the topic of several research papers, however, most of these papers only deal with pneumatic passenger and truck tires. In recent years, wheeled-scaled vehicles have gained lots of attention as a feasible testing platform, nonetheless up to the authors’ knowledge there has been no research regarding the use of scaled tires and their effect on the overall vehicle performance characteristics. This paper presents a novel scaled electric combat vehicle tire model and validation technique. The pro-line lockdown tire size 3.00 × 7.35 is modeled using the Finite Element Analysis (FEA) technique and several materials including layered membrane, beam elements, and Mooney-Rivlin for rubber. The tire-rim assembly is then described, and the rigid body analysis is presented. The tire is then validated using an in-house custom-made static tire testing machine. The tire test rig is made specifically to test the pro-line tire model and is designed and manufactured in the laboratory. The tire is validated using vertical stiffness and footprint tests in the static domain at different operating conditions including several vertical loads. Then the tire is used to perform rolling resistance and steering analysis including the rolling resistance coefficient and the cornering stiffness. The analysis is performed at different operating conditions including longitudinal speeds of 5, 10, and 15 km/h. This tire model will be further used to determine the tractive and braking performance of the tire. Furthermore, the tire test rig will also be modified to perform cornering stiffness tests.

Tire Dynamics Modeling Method Based on Rapid Test Method

Combined with the tire dynamics theoretical model,a rapid test method to obtain tire lateral and longitudinal both steady-state and transient characteristics only based on the tire quasi-steady-state test results is proposed.For steady state data extraction,the test time of the rapid test method is half that of the conventional test method.For transient tire characteristics the rapid test method omits the traditional tire test totally.At the mean time the accuracy of the two method is much closed.The rapid test method is explained theoretically and the test process is designed.The key parameters of tire are extracted and the comparison is made between rapid test and traditional test method.The result show that the identification accuracy based on the rapid test method is almost equal to the accuracy of the conventional one.Then,the heat generated during the rapid test method and that generated during the conventional test are calculated separately.The comparison shows that the heat generated during the rapid test is much smaller than the heat generated during the conventional test process.This benefits to the reduction of tire wear and the consistency of test results.Finally,it can be concluded that the fast test method can efficiently,accurately and energy-efficiently measure the steady-state and transient characteristics of the tire.

An Adaptive Nonsingular Fast Terminal Sliding Mode Control for Yaw Stability Control of Bus Based on STI Tire Model

Due to the bus characteristics of large quality,high center of gravity and narrow wheelbase,the research of its yaw stability control(YSC)system has become the focus in the field of vehicle system dynamics.However,the tire nonlinear mechanical properties and the effectiveness of the YSC control system are not considered carefully in the current research.In this paper,a novel adaptive nonsingular fast terminal sliding mode(ANFTSM)control scheme for YSC is proposed to improve the bus curve driving stability and safety on slippery roads.Firstly,the STI(Systems Technologies Inc.)tire model,which can effectively reflect the nonlinear coupling relationship between the tire longitudinal force and lateral force,is established based on experimental data and firstly adopted in the bus YSC system design.On this basis,a more accurate bus lateral dynamics model is built and a novel YSC strategy based on ANFTSM,which has the merits of fast transient response,finite time convergence and high robustness against uncertainties and external disturbances,is designed.Thirdly,to solve the optimal allocation problem of the tire forces,whose objective is to achieve the desired direct yaw moment through the effective distribution of the brake force of each tire,the robust least-squares allocation method is adopted.To verify the feasibility,effectiveness and practicality of the proposed bus YSC approach,the TruckSim-Simulink co-simulation results are finally provided.The co-simulation results show that the lateral stability of bus under special driving conditions has been significantly improved.This research proposes a more effective design method for bus YSC system based on a more accurate tire model.

Influence of vehicle-road coupled vibration on tire adhesion based on nonlinear foundation

The influence of pavement vibration on tire adhesion is of great significance to the structure design of vehicle and pavement.The adhesion between tire and road is the key to studying vehicle dynamics,and the precise description of tire adhesion affects the accuracy of dynamic vehicle responses.However,in most models,only road roughness is considered,and the pavement vibration caused by vehicle-road interaction is ignored.In this paper,a vehicle is simplified as a spring-mass-damper oscillator,and the vehicle-pavement system is modeled as a vehicle moving along an Euler-Bernoulli beam with finite length on a nonlinear foundation.The road roughness is considered as a sine wave,and the shear stress is ignored on the pavement.According to the contact form between tire and road,the LuGre tire model is established to calculate the tire adhesion force.The Galerkin method is used to simplify the partial differential equations of beam vibration into finite ordinary differential equations.A product-to-sum formula and a Dirac delt function are used to deal with the nonlinear term caused by the nonlinear foundation,which realizes the fast and accurate calculation of super-high dimensional nonlinear ordinary differential equations.In addition,the dynamic responses between the coupled system and the traditional uncoupled system are compared with each other.The obtained results provide an important theoretical basis for research on the influence of vehicle-road coupled vibration on tire adhesion.

Effect of Tire Repeated Root Modal on Tire Modelling with Experimental Modal

The effect of tire repeated root modal（RRM）on tire modeling with an experimental modal is studied.Firstly,a radial tire with radial and tangential RRMs is tested and analyzed.By multi-point exciting of the radial tire,a multiple reference frequency domain method based on a least squares（LMS PolyMAX）algorithm is used to identify modal parameters.Then,modal stability diagram（MSD）,modal indication function（MIF）and modal assurance criteria（Auto-MAC）matrix are utilized to induce multiple inputs multiple outputs（MIMO）frequency response function（FRF）matrixes.The tests reveal that notable repeated roots exist in both radial and tangential response modes.Their modal frequencies and damping factors are approximately the same,the amplitudes of modal vectors are in the same order of magnitude,and the mode shapes are orthogonal.Based on the works mentioned,the method of trigonometric series modal shapes fitting is adopted,the effects of RRM model on tire modeling with a vertical experimental modal are discussed.The final results show that the effects of considering the RRM shapes are equivalent to the tire mode shapes depended on rotating the tire’s different exciting points during tire modeling,and since considering the RRM,the tire mode shapes can be unified and fixed during tire modeling.

Coordinated Control Architecture for Motion Management in ADAS Systems

Advanced driver assistance systems(ADAS) seek to provide drivers and passengers of automotive vehicles increased safety and comfort. Original equipment manufacturers are integrating and developing systems for distance keeping, lane keeping and changing and other functionalities. The modern automobile is a complex system of systems. How the functionalities of advanced driver assistance are implemented and coordinated across the systems of the vehicle is generally not made available to the wider research community by the developers and manufactures. This paper seeks to begin filling this gap by assembling open source physics models of the vehicle dynamics and ADAS command models. Additionally, in order to facilitate ADAS development and testing without having access to the details of ADAS, a coordinated control architecture for motion management is also proposed for distributing ADAS motion control commands over vehicle systems. The architecture is demonstrated in a case study where motion is coordinated between the steering and the braking systems, which are typically used only for a single functionality. The integrated vehicle and system dynamics using the coordinated control architecture are simulated for various driving tasks. It is seen that improved trajectory following can be achieved by the proposed coordinated control architecture. The models, simulations and control architecture are made available for open access.

Control Research for a Small Fixed-Wing UAV DuringGround Taxiing

Ground taxiing is the key process of take-off and landing for a tricycle-undercarriage unmanned aerial vehicle( UAV). Nonlinear model of a sample UAV is established based on stiffness and damping model of landing gears and tires taken into account. Then lateral nonlinear model is linearized and state space equations are deduced by using nose wheel and ruder as inputs and lateral states as outputs. Adaptive internal model control( AIMC) is proposed and applied to lateral control based on decoupled and linearized dynamic model during ground taxiing process. Different control strategies are analyzed and compared by simulations,and then a combined control strategy of nose wheel steering with holding and rudder control is given. Hardware in loop simulations( HILS) proves the validity of the controller designed.

A Discrete Tire Model for Cornering Properties Considering Rubber Friction

In this paper,a discrete tire model of comering properties for road vehicles relating to tire grip performance,which is important for driving stability and safety,is presented.The proposed tire model combines realistic rubber friction related to velocity and tire grip performance with deformation of the carcass.The model can describe the stress and strain of the carcass and tread,and the rubber friction coefficient at each point of the contact patch,which is affected by the di stribution of the slip velocity.Meanwhile,the model incorporates the effects of the viscoelastic rubber material and power spectrum of the road,which are explicitly reflected in the rubber friction model.First,an improved rubber friction model based on the Persson theory of rubber friction is introduced in this paper.A discrete analytical tire model,which considers carcass compliance and the discretization of the tread,is then proposed.In addition,important phenomena of tire properties arising from the carcass compl iance and rubber friction are analyzed and the effectiveness of the discrete analytical tire model is validated experimentally.The proposed model provides a new way to optimize the grip performance of a tire by adjusting the tire or rubber physical parameters even before the tire is made.

Parameter Identification of Magic Formula Tire Model Based on Fibonacci Tree Optimization Algorithm

The magic formula(MF)tire model is a semi-empirical tire model that can precisely simulate tire behavior.The heuristic optimization algorithm is typically used for parameter identification of the MF tire model.To avoid the defect of the traditional heuristic optimization algorithm that can easily fall into the local optimum,a parameter identification method based on the Fibonacci tree optimization(FTO)algorithm is proposed,which is used to identify the parameters of the MF tire model.The proposed method establishes the basic structure of the Fibonacci tree alternately through global and local searches and completes optimization accordingly.The global search rule in the original FTO was modified to improve its efficiency.The results of independent repeated experiments on two typical multimodal function optimizations and the parameter identification results showed that FTO was not sensitive to the initial values.In addition,it had a better global optimization performance than genetic algorithm(GA)and particle swarm optimization(PSO).The root mean square error values optimized with FTO were 5.09%,10.22%,and 3.98%less than the GA,and 6.04%,4.47%,and 16.42%less than the PSO in pure lateral and longitudinal forces,and pure aligning torque parameter identification.The parameter identification method based on FTO was found to be effective.

A dynamic tire model based on HPSO-SVM

In order to accurately describe the force mechanism of tires on agricultural roads and improve the life cycle of agricultural tires,a tire-deformable terrain model was established.The effects of tread pattern,wheel spine,tire sidewall elasticity,inflation pressure and soil deformation were considered in the model and fitted with a support vector machine(SVM)model.Hybrid particle swarm optimization(HPSO)was used to optimize the parameters of SVM prediction model,of which inertia weight and learning factor were improved.To verify the performance of the model,a tire force prediction model of agricultural vehicle with the improved SVM method was investigated,which was a complex nonlinear problem affected by many factors.Cross validation(CV)method was used to evaluate the training precision accuracy of the model,and then the improved HPSO was adopted to select parameters.Results showed that the choice randomness of specifying the parameters was avoided and the workload of the parameter selection was reduced.Compared with the dynamic tire model without considering the influence of tread pattern and wheel spine,the improved SVM model achieved a better prediction performance.The empirical results indicate that the HPSO based parameters optimization in SVM is feasible,which provides a practical guidance to tire force prediction of agricultural transport vehicles.

Ground maneuver for front-wheel drive aircraft via deep reinforcement learning

The maneuvering time on the ground accounts for 10%–30%of their flight time,and it always exceeds 50%for short-haul aircraft when the ground traffic is congested.Aircraft also contribute significantly to emissions,fuel burn,and noise when taxiing on the ground at airports.There is an urgent need to reduce aircraft taxiing time on the ground.However,it is too expensive for airports and aircraft carriers to build and maintain more runways,and it is space-limited to tow the aircraft fast using tractors.Autonomous drive capability is currently the best solution for aircraft,which can save the maneuver time for aircraft.An idea is proposed that the wheels are driven by APU-powered(auxiliary power unit)motors,APU is working on its efficient point;consequently,the emissions,fuel burn,and noise will be reduced significantly.For Front-wheel drive aircraft,the front wheel must provide longitudinal force to tow the plane forward and lateral force to help the aircraft make a turn.Forward traction effects the aircraft’s maximum turning ability,which is difficult to be modeled to guide the controller design.Deep reinforcement learning provides a powerful tool to help us design controllers for black-box models;however,the models of related works are always simplified,fixed,or not easily modified,but that is what we care about most.Only with complex models can the trained controller be intelligent.High-fidelity models that can easily modified are necessary for aircraft ground maneuver controller design.This paper focuses on the maneuvering problem of front-wheel drive aircraft,a high-fidelity aircraft taxiing dynamic model is established,including the 6-DOF airframe,landing gears,and nonlinear tire force model.A deep reinforcement learning based controller was designed to improve the maneuver performance of front-wheel drive aircraft.It is proved that in some conditions,the DRL based controller outperformed conventional look-ahead controllers.