科创中国

依据故障树分析法(VIA)原理,对城市轨道交通车辆维修的安全故障因素进行了分析.城市轨道交通车辆维修的工艺过程存在着安全"风险累积"效应;维修后车辆的营运过程存在着"风险扩散"效应.在分析目前城市轨道交通车辆维修面临挑战的基础上,提出了风险应急和风险控制的相应对策.

The existing research of the active suspension system(ASS) mainly focuses on the different evaluation indexes and control strategies. Among the different components, the nonlinear characteristics of practical systems and control are usually not considered for vehicle lateral dynamics. But the vehicle model has some shortages on tyre model with side-slip angle, road adhesion coefficient, vertical load and velocity. In this paper, the nonlinear dynamic model of lateral system is considered and also the adaptive neural network of tire is introduced. By nonlinear analysis methods, such as the bifurcation diagram and Lyapunov exponent, it has shown that the lateral dynamics exhibits complicated motions with the forward speed. Then, a fuzzy control method is applied to the lateral system aiming to convert chaos into periodic motion using the linear-state feedback of an available lateral force with changing tire load. Finally, the rapid control prototyping is built to conduct the real vehicle test. By comparison of time response diagram, phase portraits and Lyapunov exponents at different work conditions, the results on step input and S-shaped road indicate that the slip angle and yaw velocity of lateral dynamics enter into stable domain and the results of test are consistent to the simulation and verified the correctness of simulation. And the Lyapunov exponents of the closed-loop system are becoming from positive to negative. This research proposes a fuzzy control method which has sufficient suppress chaotic motions as an effective active suspension system.

The existing research of the integrated chassis control mainly focuses on the different evaluation indexes and control strategy. Among the different evaluation indexes, the comprehensive properties are usually not considered based on the non-linear superposition principle. But, the control strategy has some shortages on tyre model with side-slip angle, road adhesion coefficient, vertical load and velocity. In this paper, based on belief, desire and intention(BDI)-agent model framework, the TYRE agent, electric power steering(EPS) agent and active suspension system(ASS) agent are proposed. In the system(SYS) agent, the coordination mechanism is employed to manage interdependences and conflicts among other agents, so as to improve the flexibility, adaptability, and robustness of the global control system. Due to the existence of the simulation demand of dynamic performance, the vehicle multi-body dynamics model is established by SIMPACK. And then the co-simulation analysis is conducted to evaluate the proposed multi-agent system(MAS) controller. The simulation results demonstrate that the MAS has good effect on the performance of EPS and ASS. Meantime, the better road feeling for the driver is provided considering the multiple and complex driving traffic. Finally, the MAS rapid control prototyping is built to conduct the real vehicle test. The test results are consistent to the simulation results, which verifies the correctness of simulation. The proposed research ensures the driving safety, enhances the handling stability, and improves the ride comfort.

The existing investigations on thermal comfort mostly focus on the thermal environment conditions, especially of the air-flow field and the temperature distributions in vehicle cabin. Less attention appears to direct to the thermal comfort or thermal sensation of occupants, even to the relationship between thermal conditions and thermal sensation. In this paper, a series of experiments were designed and conducted for understanding the non-uniform conditions and the occupant's thermal responses in vehicle cabin during the heating period. To accurately assess the transient temperature distribution in cabin in common daily condition, the air temperature at a number of positions is measured in a full size vehicle cabin under natural winter environment in South China by using a discrete thermocouples network. The occupant body is divided into nine segments, the skin temperature at each segment and the occupant's local thermal sensation at the head, body, upper limb and lower limb are monitored continuously. The skin temperature is observed by using a discrete thermocouples network, and the local thermal sensation is evaluated by using a seven-point thermal comfort survey questionnaire proposed by American Society of Heating, Refrigerating and Air-Conditioning Engineers, Inc(ASHRAE) Standard. The relationship between the skin temperature and the thermal sensation is discussed and regressed by statistics method. The results show that the interior air temperature is highly non-uniform over the vehicle cabin. The locations where the occupants sit have a significant effect on the occupant's thermal responses, including the skin temperature and the thermal sensation. The skin temperature and thermal sensation are quite different between body segments due to the effect of non-uniform conditions, clothing resistance, and the human thermal regulating system. A quantitative relationship between the thermal sensation and the skin temperature at each body segment of occupant in real life traffic is presented. The investigation result indicates that the skin temperature is a robust index to evaluate the thermal sensation. Applying the skin temperature to designing and controlling parameters of the heating, ventilation and air conditioning(HVAC) system may benefit the thermal comfort and reducing energy consumption.

The major methods to investigate the airbags cushion system are experimental method,thermodynamic method and finite element method(FEM).Airbags cushion systems are very complicated and very difficult to be investigated thoroughly by such methods.For experimental method,it is nearly impossible to completely analyze and optimize the cushion characteristics of airbags of airborne vehicle because of charge issue,safety concern and time constraint.Thermodynamic method fails to take the non-linear effects of large airbag deformation and varied contact conditions into consideration.For finite element method,the FE model is usually complicated and the calculation takes tens of hours of CPU time.As a result,the optimization of the design based on a nonlinear model is very difficult by traditional iterative approach method.In this paper,a model based on FEM and control volume method is proposed to simulate landing cushion process of airborne vehicle with airbags cushion system in order to analyze and optimize the parameters in airbags cushion system.At first,the performance of airbags cushion system model is verified experimentally.In airdrop test,accelerometers are fixed in 4 test points distributed over engine mount,top,bottom and side armor plate of hull to obtain acceleration curves with time.The simulation results are obtained under the same conditions of the airdrop test and the simulation results agree very well with the experimental results,which indicate the established model is valid for further optimization.To optimize the parameters of airbags,equivalent response model based on Latin Hypercube DOE and radial basis function is employed instead of the complex finite element model.Then the optimal results based on equivalent response model are obtained using simulated annealing algorithm.After optimization,the maximal acceleration of airborne vehicle landing reduces 19.83%,while the energy absorption by airbags increases7.85%.The performance of the airbags cushion system thus is largely improved through optimization,which indicates the proposed method has the capability of solving the parameter optimization problem of airbags cushion system for airborne vehicle.

The current research of real-time observation for vehicle roll steer angle and compliance steer angle(both of them comprehensively referred as the additional steer angle in this paper) mainly employs the linear vehicle dynamic model, in which only the lateral acceleration of vehicle body is considered. The observation accuracy resorting to this method cannot meet the requirements of vehicle real-time stability control, especially under extreme driving conditions. The paper explores the solution resorting to experimental method. Firstly, a multi-body dynamic model of a passenger car is built based on the ADAMS/Car software, whose dynamic accuracy is verified by the same vehicle's roadway test data of steady static circular test. Based on this simulation platform, several influencing factors of additional steer angle under different driving conditions are quantitatively analyzed. Then ε-SVR algorithm is employed to build the additional steer angle prediction model, whose input vectors mainly include the sensor information of standard electronic stability control system(ESC). The method of typical slalom tests and FMVSS 126 tests are adopted to make simulation, train model and test model's generalization performance. The test result shows that the influence of lateral acceleration on additional steer angle is maximal(the magnitude up to 1°), followed by the longitudinal acceleration-deceleration and the road wave amplitude(the magnitude up to 0.3°). Moreover, both the prediction accuracy and the calculation real-time of the model can meet the control requirements of ESC. This research expands the accurate observation methods of the additional steer angle under extreme driving conditions.

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.