Stability-Considered Lane Keeping Control of Commercial Vehicles Based on Improved APF Algorithm

Regarding the lane keeping system,path tracking accuracy and lateral stability at high speeds need to be taken into account especially for commercial vehicles due to the characteristics of larger mass,longer wheelbase and higher mass center.To improve the performance mentioned above comprehensively,the control strategy based on improved artificial potential field(APF)algorithm is proposed.In the paper,time to lane crossing(TLC)is introduced into the potential field function to enhance the accuracy of path tracking,meanwhile the vehicle dynamics parameters including yaw rate and lateral acceleration are chosen as the repulsive force field source.The lane keeping controller based on improved APF algorithm is designed and the stability of the control system is proved based on Lyapunov theory.In addition,adaptive inertial weight particle swarm optimization algorithm(AIWPSO)is applied to optimize the gain of each potential field function.The co-simulation results indicate that the comprehensive evaluation index respecting lane tracking accuracy and lateral stability is reduced remarkably.Finally,the proposed control strategy is verified by the HiL test.It provides a beneficial reference for dynamics control of commercial vehicles and enriches the theoretical development and practical application of artificial potential field method in the field of intelligent driving.

A Novel Prescribed-Performance Path-Following Problem for Non-Holonomic Vehicles

The issue of achieving prescribed-performance path following in robotics is addressed in this paper,where the aim is to ensure that a desired path within a specified region is accu-rately converged to by the controlled vehicle.In this context,a novel form of the prescribed performance guiding vector field is introduced,accompanied by a prescribed-time sliding mode con-trol approach.Furthermore,the interdependence among the pre-scribed parameters is discussed.To validate the effectiveness of the proposed method,numerical simulations are presented to demonstrate the efficacy of the approach.

LSDA-APF:A Local Obstacle Avoidance Algorithm for Unmanned Surface Vehicles Based on 5G Communication Environment

In view of the complex marine environment of navigation,especially in the case of multiple static and dynamic obstacles,the traditional obstacle avoidance algorithms applied to unmanned surface vehicles(USV)are prone to fall into the trap of local optimization.Therefore,this paper proposes an improved artificial potential field(APF)algorithm,which uses 5G communication technology to communicate between the USV and the control center.The algorithm introduces the USV discrimination mechanism to avoid the USV falling into local optimization when the USV encounter different obstacles in different scenarios.Considering the various scenarios between the USV and other dynamic obstacles such as vessels in the process of performing tasks,the algorithm introduces the concept of dynamic artificial potential field.For the multiple obstacles encountered in the process of USV sailing,based on the International Regulations for Preventing Collisions at Sea(COLREGS),the USV determines whether the next step will fall into local optimization through the discriminationmechanism.The local potential field of the USV will dynamically adjust,and the reverse virtual gravitational potential field will be added to prevent it from falling into the local optimization and avoid collisions.The objective function and cost function are designed at the same time,so that the USV can smoothly switch between the global path and the local obstacle avoidance.The simulation results show that the improved APF algorithm proposed in this paper can successfully avoid various obstacles in the complex marine environment,and take navigation time and economic cost into account.

Path planning for unmanned aerial vehicles in surveillance tasks under wind fields

The optimal path planning for fixed-wing unmanned aerial vehicles(UAVs) in multi-target surveillance tasks(MTST) in the presence of wind is concerned.To take into account the minimal turning radius of UAVs,the Dubins model is used to approximate the dynamics of UAVs.Based on the assumption,the path planning problem of UAVs in MTST can be formulated as a Dubins traveling salesman problem(DTSP).By considering its prohibitively high computational cost,the Dubins paths under terminal heading relaxation are introduced,which leads to significant reduction of the optimization scale and difficulty of the whole problem.Meanwhile,in view of the impact of wind on UAVs' paths,the notion of virtual target is proposed.The application of the idea successfully converts the Dubins path planning problem from an initial configuration to a target in wind into a problem of finding the minimal root of a transcendental equation.Then,the Dubins tour is derived by using differential evolution(DE) algorithm which employs random-key encoding technique to optimize the visiting sequence of waypoints.Finally,the effectiveness and efficiency of the proposed algorithm are demonstrated through computational experiments.Numerical results exhibit that the proposed algorithm can produce high quality solutions to the problem.

Analysis on Thermal Current Field in Powertrain Cabin of Tracked Vehicles With Electric Transmission System Configuration-2

The electric transmission system congfiguration-2 is one of the main electric drives for tracked vehicles. The geometrical model for the power-train cabin is established and the preliminary design for its cooling system is implemented. The mathematic model is established for thermal current field computation, simulation and analysis in the powertrain cabin. The three-dimensional structure of the powertrain cabin is optimized. The validity of the cooling system design is proved. The foundation for optimizing the whole electric transmission system configuration is laid.

Numerical Simulation of Airflow Field and Structure Improvement in Engine Compartment of Armored Vehicles with Electric Transmission

When the mechanical drive is changed into the electric transmission,the cooling system of the engine compartment should be altered to meet the new requirement for the increasing in equipment such as electric apparatus.In order to predict and analyze the rationality of cooling system in the virtual engine compartment,the numerical simulation of airflow fields in the engine compartment by using computational fluid dynamics(CFD) technique is necessary.An armored vehicle with electric transmission in the research is taken as the research object.The physical model and mathematical model for the computation of 3D air flow and heat transfer in the engine compartment of an armored vehicle with electric transmission is established.Turbulent flow in the compartment is described by using the standard k-ε two-equation turbulence model.The temperature and velocity fields of 3D air flow in the engine compartment are numerically simulated and analyzed based on different fan's flux.A theoretical basis for determination of the fan's flux is given by the simulation results.The positions of the air-vent shutter are analyzed.The simulation results show that the different positions of the air-vent shutter can lead to different cooling efficiencies.

Video-based vehicle tracking considering occlusion

To track the vehicles under occlusion, a vehicle tracking algorithm based on blocks is proposed. The target vehicle is divided into several blocks of uniform size, in which the edge block can overlap its neighboring blocks. All the blocks＇ motion vectors are estimated, and the noise motion vectors are detected and adjusted to decrease the error of motion vector estimation. Then, by moving the blocks based on the adjusted motion vectors, the vehicle is tracked. Aiming at the occlusion between vehicles, a Markov random field is established to describe the relationship between the blocks in the blocked regions. The neighborhood of blocks is defined using the Euclidean distance. An energy function is defined based on the blocks＇ histograms and optimized by the simulated annealing algorithm to segment the occlusion region. Experimental results demonstrate that the proposed algorithm can track vehicles under occlusion accurately.

Driving and Braking Control of PM Synchronous Motor Based on Low-resolution Hall Sensor for Battery Electric Vehicle

Resolvers are normally employed for rotor positioning in motors for electric vehicles, but resolvers are expensive and vulnerable to vibrations. Hall sensors have the advantages of low cost and high reliability, but the positioning accuracy is low. Motors with Hall sensors are typically controlled by six-step commutation algorithm, which brings high torque ripple. This paper studies the high-performance driving and braking control of the in-wheel permanent magnetic synchronous motor （PMSM） based on low-resolution Hall sensors. Field oriented control （FOC） based on Hall-effect sensors is developed to reduce the torque ripple. The positioning accuracy of the Hall sensors is improved by interpolation between two consecutive Hall signals using the estimated motor speed. The position error from the misalignment of the Hall sensors is compensated by the precise calibration of Hall transition timing. The braking control algorithms based on six-step commutation and FOC are studied. Two variants of the six-step commutation braking control, namely, half-bridge commutation and full-bridge commutation, are discussed and compared, which shows that the full-bridge commutation could better explore the potential of the back electro-motive forces （EMF）, thus can deliver higher efficiency and smaller current ripple. The FOC braking is analyzed with the phasor diagrams. At a given motor speed, the motor turns from the regenerative braking mode into the plug braking mode if the braking torque exceeds a certain limit, which is proportional to the motor speed. Tests in the dynamometer show that a smooth control could be realized by FOC driving control and the highest efficiency and the smallest current ripple could be achieved by FOC braking control, compared to six-step commutation braking control. Therefore, FOC braking is selected as the braking control algorithm for electric vehicles. The proposed research ensures a good motor control performance while maintaining low cost and high reliability.

ENERGY MANAGEMENT STRATEGY FOR PARALLEL HYBRID ELECTRIC VEHICLES

Energy management strategy (EMS) is the core of the real-time controlalgorithm of the hybrid electric vehicle (HEV). A novel EMS using the logic threshold approach withincorporation of a stand-by optimization algorithm is proposed. The aim of it is to minimize theengine fuel consumption and maintain the battery state of charge (SOC) in its operation range, whilesatisfying the vehicle performance and drivability requirements. The hybrid powertrain bench testis carried out to collect data of the engine, motor and battery pack, which are used in the EMS tocontrol the powertrain. Computer simulation model of the HEV is established in the MATLAB/Simulinkenvironment according to the bench test results. Simulation results are presented for behaviors ofthe engine, motor and battery. The proposed EMS is implemented for a real parallel hybrid carcontrol system and validated by vehicle field tests.

Towards the Unified Principles for Level 5 Autonomous Vehicles

The rapid advance of autonomous vehicles(AVs)has motivated new perspectives and potential challenges for existing modes of transportation.Currently,driving assistance systems of Level 3 and below have been widely produced,and several applications of Level 4 systems to specific situations have also been gradually developed.By improving the automation level and vehicle intelligence,these systems can be further advanced towards fully autonomous driving.However,general development concepts for Level 5 AVs remain unclear,and the existing methods employed in the development processes of Levels 0-4 have been mainly based on task-driven function development related to specific scenarios.Therefore,it is difficult to identify the problems encountered by high-level AVs.The essential logical and physical mechanisms of vehicles have hindered further progression towards Level 5 systems.By exploring the physical mechanisms behind high-level autonomous driving systems and analyzing the essence of driving,we put forward a coordinated and balanced framework based on the brain-cerebellum-organ concept through reasoning and deduction.Based on a mixed mode relying on the crow inference and parrot imitation approach,we explore the research paradigm of autonomous learning and prior knowledge to realize the characteristics of self-learning,self-adaptation,and self-transcendence for AVs.From a systematic,unified,and balanced point of view and based on least action principles and unified safety field concepts,we aim to provide a novel research concept and develop an effective approach for the research and development of high-level AVs,specifically at Level 5.

Test and numerical investigations on static and dynamic characteristics of extra-wide concrete self-anchored suspension bridge under vehicle loads

The present work is aimed at studying the mechanic properties of the extra-wide concrete self-anchored suspension bridge under static and dynamic vehicle loads. Based on the field test using 12 heavy trucks and finite element simulations, the static deformations of different components, stress increments and distributions of the girder, as well as the vibration characteristics and damping ratio of the Hunan Road Bridge were analyzed, which is the widest self-anchored suspension bridge in China at present. The dynamic responses were calculated using the Newmark-β integration method assisted by the simulation models of bridge and vehicles, the influences on the dynamic impact coefficient(DIC) brought by the vehicle parameters, girder width, eccentricity travel and deck flatness were also researched. The spatial effect of the girder is obvious due to the extra width, which performs as the stress increments distribute unevenly along the transverse direction, and the girder deflections and stress increments of the upper plate change as a "V" and "M" shape respectively under the symmetrical vehicle loads affected by the shear lag effect, cross slope and local effect of the wheels, the maximum of stress increments are located in the junctions with the inner webs. The obvious girder torsional deformation and the apparent unevenness of the hanger forces between the two cable planes under the eccentric vehicle loads, together with the mode shapes such as the girder transverse bending and torsion which appear relatively earlier, all reflect the weakened torsional rigidity of the extra-wide girder. The transverse displacements of towers are more obvious than the longitudinal ones. As for the influences on the DIC, the static effect of the heavier vehicles plays a major role when pass through with a higher speed and the changes of vehicle suspension stiffness generate greater impacts than the suspension damp. The values of DIC in the vehicle-running side during the eccentric travel, affected by the restricts from the static effects of the eccentric moving trucks, are significantly smaller than the vehicle-free side, the increase in the road roughness is the most sensitive one among the above influential factors. The results could provide references for the design, static and dynamic response analysis of the similar extra-wide suspension bridges.

Numerical computation and analysis of unsteady viscous flow around autonomous underwater vehicle with propellers based on sliding mesh

The flexible transmission shaft and wheel propeller are combined as the kinetic source equipment, which realizes the nmlti-motion modes of the autonomous underwater vehicle （AUV） such as vectored thruster and wheeled movement. In order to study the interactional principle between the hull and the wheel propellers while the AUV navigating in water, the computational fluid dynamics （CFD） method is used to simulate numerically the unsteady viscous flow around AUV with propellers by using the Reynolds-averaged Navier-Stokes （RANS） equations, shear-stress transport （SST） k-w model and pressure with splitting of operators （PISO） algorithm based on sliding mesh. The hydrodynamic parameters of AUV with propellers such as resistance, pressure and velocity are got, which reflect well the real ambient flow field of AUV with propellers. Then, the semi-implicit method for pressure-linked equations （SIMPLE） algorithm is used to compute the steady viscous flow field of AUV hull and propellers, respectively. The computational results agree well with the experimental data, which shows that the numerical method has good accuracy in the prediction of hydrodynamic performance. The interaction between AUV hull and wheel propellers is predicted qualitatively and quantitatively by comparing the hydrodynamic parameters such as resistance, pressure and velocity with those from integral computation and partial computation of the viscous flow around AUV with propellers, which provides an effective reference to the shady on noise and vibration of AUV hull and propellers in real environment. It also provides technical support for the design of new AUVs.

Experimental investigation on vibration characteristics of the medium-low-speed maglev vehicle-turnout coupled system

The steel turnout is one of the key components in the medium–low-speed maglev line system.However,the vehicle under active control is prone to vehicle–turnout coupled vibration,and thus,it is necessary to identify the vibration characteristics of this coupled system through field tests.To this end,dynamic performance tests were conducted on a vehicle–turnout coupled system in a medium–low-speed maglev test line.Firstly,the dynamic response data of the coupled system under various operating conditions were obtained.Then,the natural vibration characteristics of the turnout were analysed using the free attenuation method and the finite element method,indicating a good agreement between the simulation results and the measured results;the acceleration response characteristics of the coupled system were analysed in detail,and the ride quality of the vehicle was assessed by Sperling index.Finally,the frequency distribution characteristics of the coupled system were discussed.All these test results could provide references for model validation and optimized design of medium–low-speed maglev transport systems.

Torque-based Optimal Acceleration Control for Electric Vehicle

The existing research of the acceleration control mainly focuses on an optimization of the velocity trajectory with respect to a criterion formulation that weights acceleration time and fuel consumption. The minimum-fuel acceleration problem in conventional vehicle has been solved by Pontryagin＇s maximum principle and dynamic programming algorithm, respectively. The acceleration control with minimum energy consumption for battery electric vehicle（EV） has not been reported. In this paper, the permanent magnet synchronous motor（PMSM） is controlled by the field oriented control（FOC） method and the electric drive system for the EV（including the PMSM, the inverter and the battery） is modeled to favor over a detailed consumption map. The analytical algorithm is proposed to analyze the optimal acceleration control and the optimal torque versus speed curve in the acceleration process is obtained. Considering the acceleration time, a penalty function is introduced to realize a fast vehicle speed tracking. The optimal acceleration control is also addressed with dynamic programming（DP）. This method can solve the optimal acceleration problem with precise time constraint, but it consumes a large amount of computation time. The EV used in simulation and experiment is a four-wheel hub motor drive electric vehicle. The simulation and experimental results show that the required battery energy has little difference between the acceleration control solved by analytical algorithm and that solved by DP, and is greatly reduced comparing with the constant pedal opening acceleration. The proposed analytical and DP algorithms can minimize the energy consumption in EV＇s acceleration process and the analytical algorithm is easy to be implemented in real-time control.

Optimization of the Heat Dissipation Structure and Temperature Distribution in an Electric Vehicle Power Battery

In order to ensure that the lithium-ion battery pack keeps good working performance during the driving of electric vehicle,the heat generation mechanism and heat transfer characteristics of lithium-ion battery are analyzed.The power battery pack of electric vehicle is simulated by advanced vehicle simulator.The simulation results of battery pack current under typical cycle conditions and the heat source curve of lithium ion battery are obtained,which provide data for the simulation of heat source input of battery temperature field.On this basis,the flow field and temperature field of the original lithium-ion battery pack of electric vehicle are simulated by using computational fluid dynamics method.The influence of different air passage spacing and air inlet angle on the temperature field of lithium ion battery pack was analyzed.The optimization scheme of heat dissipation structure of lithium ion battery pack was put forward,and the numerical simulation analysis of the optimization scheme was carried out.The results show that the heat dissipation effect of the heat dissipation structure is obviously improved by choosing the appropriate air inlet and the combined air passage spacing,and it is beneficial to the uniformity of the temperature of the single battery.The maximum temperature of the battery pack is reduced by 3.8℃,and the temperature difference of the battery pack is reduced by 2.2℃.

Development of High Torque and High Power Density Hybrid Excitation Flux Switching Motor for Traction Drive in Hybrid Electric Vehicles

This paper presents design feasibility study and development of a new hybrid excitation flux switching motor (HEFSM) as a contender for traction drives in hybrid electric vehicles (HEVs). Initially, the motor general construction, the basic working principle and the design concept of the proposed HEFSM are outlined. Then, the initial drive performances of the proposed HEFSM are evaluated based on 2D-FEA, in which the design restrictions, specifications and target performances are similar with conventional interior permanent magnet synchronous motor (IPMSM) used in HEV. Since the initial results fail to achieve the target performances, deterministic design optimization approach is used to treat several design parameters. After several cycles of optimization, the proposed motor makes it possible to obtain the target torque and power of 333 Nm and 123 kW, respectively. In addition, due to definite advantage of robust rotor structure of HEFSM, rotor mechanical stress prediction at maximum speed of 12,400 r/min is much lower than the mechanical stress in conventional IPMSM. Finally, the maximum torque and power density of the final design HEFSM are approximately 11.41 Nm/kg and 5.55 kW/kg, respectively, which is 19.98% and 58.12% more than the torque and power density in existing IPMSM for Lexus RX400h.

Structural Design and Static Stress Analysis of Dead Pig Vehicle

Nowadays,in our pig field there has no special device to transport those dead pigs. In normal condition,we need some person to carry out those dead pigs from the pig field.But considering the narrow aisle,manual handling is not convenient,on one hand,these measures will increase the labor costs,on the other hand,these measures will increase the labor intensity of workers. In order to carry out those dead pigs from the pig field fast and efficient,to achieve the purpose of health cultivation,in this paper,we designed a dead pig vehicle to handle those dead pigs. The dead pig vehicle consists of chassis,lifting device,driving device,rotating device,power system and control system. The vehicle adopts self-propelled structure,which is equipped with two lead-acid batteries as power. Loading,transportation,unloading and other dead pig handling full operations can finished by only one person. The result of simulation shows that the dead pig vehicle has a good performance and a good stability,it also can satisfy the requirements of the narrow aisle. The results of this research can provide reference for the similar transportation vehicles.

Model calibration concerning risk coefficients of driving safety field model

Driving safety field(DSF) model has been proposed to represent comprehensive driving risk formed by interactions of driver-vehicle-road in mixed traffic environment. In this work, we establish an optimization model based on grey relation degree analysis to calibrate risk coefficients of DSF model. To solve the optimum solution, a genetic algorithm is employed. Finally, the DSF model is verified through a real-world driving experiment. Results show that the DSF model is consistent with driver's hazard perception and more sensitive than TTC. Moreover, the proposed DSF model offers a novel way for criticality assessment and decision-making of advanced driver assistance systems and intelligent connected vehicles.

Cooperative Search of UAV Swarm Based on Ant Colony Optimization with Artificial Potential Field

An ant colony optimization with artificial potential field(ACOAPF)algorithm is proposed to solve the cooperative search mission planning problem of unmanned aerial vehicle(UAV)swarm.This algorithm adopts a distributed architecture where each UAV is considered as an ant and makes decision autonomously.At each decision step,the ants choose the next gird according to the state transition rule and update its own artificial potential field and pheromone map based on the current search results.Through iterations of this process,the cooperative search of UAV swarm for mission area is realized.The state transition rule is divided into two types.If the artificial potential force is larger than a threshold,the deterministic transition rule is adopted,otherwise a heuristic transition rule is used.The deterministic transition rule can ensure UAVs to avoid the threat or approach the target quickly.And the heuristics transition rule considering the pheromone and heuristic information ensures the continuous search of area with the goal of covering more unknown area and finding more targets.Finally,simulations are carried out to verify the effectiveness of the proposed ACOAPF algorithm for cooperative search mission of UAV swarm.

Underwater square-root cubature attitude estimator by use of quaternion-vector switching and geomagnetic field tensor

This paper presents a kind of attitude estimation algorithm based on quaternion-vector switching and square-root cubature Kalman filter for autonomous underwater vehicle(AUV).The filter formulation is based on geomagnetic field tensor measurement dependent on the attitude and a gyro-based model for attitude propagation. In this algorithm, switching between the quaternion and the three-component vector is done by a couple of the mathematical transformations. Quaternion is chosen as the state variable of attitude in the kinematics equation to time update, while the mean value and covariance of the quaternion are computed by the three-component vector to avoid the normalization constraint of quaternion. The square-root forms enjoy a continuous and improved numerical stability because all the resulting covariance matrices are guaranteed to stay positively semidefinite. The entire square-root cubature attitude estimation algorithm with quaternion-vector switching for the nonlinear equality constraint of quaternion is given. The numerical simulation of simultaneous swing motions in the three directions is performed to compare with the three kinds of filters and the results indicate that the proposed filter provides lower attitude estimation errors than the other two kinds of filters and a good convergence rate.