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The study and prevention of unstable vibration is a challenging task for vehicle industry. Improving predicting accuracy of braking squeal model is of great concern. Closed-loop coupling disc brake model is widely used in complex eigenvalue analysis and further analysis. The coupling stiffness of disc rotor and pads is one of the most important parameters in the model. But in most studies the stiffness is calculated by simple static force-deformation simulation. In this paper, a closed-loop coupling disc brake model is built. Initial values of coupling stiffness are estimated from static calculation. Experiment modal analysis of stationary disc brake system with brake line pressure and brake torques applied is conducted. Then an optimization process is initiated to minimize the differences between modal frequencies predicted by the stationary model and those from test. Thus model parameters more close to reality are found.

A computational fluid dynamics (CFD) guided design optimization was conducted for the piston bowl geometry for a heavy-duty diesel engine. The optimization goal was to minimize engine-out NOx emissions without sacrificing engine peak power and thermal efficiency. The CFD model was validated with experiments and the combustion system optimization was conducted under three selected operating conditions representing low speed, maximum torque, and rated power. A hundred piston bowl shapes were generated, of which 32 shapes with 3 spray angles for each shape were numerically analyzed and one optimized design of piston bowl geometry with spray angle was selected. On average, the optimized combustion system decreased nitrogen oxide (NOx) emissions by 17% and soot emissions by 41% without compromising maximum engine power and fuel economy.

The interactions between automatic controls, physics, and driver is an important step towards highly automated driving. This study investigates the dynamical interactions between human-selected driving modes, vehicle controller and physical plant parameters, to determine how to optimally adapt powertrain control to different human-like driving requirements. A cyber-physical system (CPS) based framework is proposed for co-design optimization of the physical plant parameters and controller variables for an electric powertrain, in view of vehicle’s dynamic performance, ride comfort, and energy efficiency under different driving modes. System structure, performance requirements and constraints, optimization goals and methodology are investigated. Intelligent powertrain control algorithms are synthesized for three driving modes, namely sport, eco, and normal modes, with appropriate protocol selections. The performance exploration methodology is presented.

Traffic congestions are increasingly severe in urban areas, especially at the merging areas of the ramps and the arterial roads. Because of the complex conflict relationship of the vehicles in ramps and arterial roads in terms of time-spatial constraints, it is challenging to coordinate the motion of these vehicles, which may easily cause congestions at the merging areas. The connected and automated vehicles (CAVs) provides potential opportunities to solve this problem. A centralized merging control method for CAVs is proposed in this paper, which can organize the traffic movements in merging areas efficiently and safely. In this method, the merging control model is built to formulate the vehicle coordination problem in merging areas, which is then transformed to the discrete nonlinear optimization form. A simulation model is built to verify the proposed method.

Studying drifting dynamics and control could extend the usable state-space beyond handling limits and maximize the potential safety benefits of autonomous vehicles. Distributed electric vehicles provide more possibilities for drifting control with better grip and larger maximum drift angle. Under the state of drifting, the distributed electric vehicle is a typical nonlinear over-actuated system with actuator redundancy, and the coupling of input vectors impedes the direct use of control algorithm of upper. This paper proposes a novel automated drifting controller for the distributed electric vehicle. First, the nonlinear over-actuated system, comprised of driving system, braking system and steering system, is formulated and transformed to a square system through proposed integrative recombination method of control channel, making general nonlinear control algorithms suitable for this system.

The large amount of controllable fuel injection parameters of Diesel engine equipped with high pressure common-rail fuel injection system makes the control of combustion more flexible, and also makes the workload of calibration and optimization much heavier. For higher efficiency, model-based approaches are presented and researched. This contribution presents a new method for modeling which is constituted by Neural Network and Adaptive Network-based Fussy Inference System (ANFIS). The experiment is carried out on a 6-cylinder common rail diesel engine. The analysis and experiment show that effective modeling can be achieved using this method.

Road test simulation on test rig is widely used in the automobile industry to shorten the development circles. However, there is still room for further improving the time cost of current road simulation test. This paper described a new method considering both the damage error and the runtime of the test on a multi-axial test rig. First, the fatigue editing technique is applied to cut the small load in road data to reduce the runtime initially. The edited road load data could be reproduced on a multi-axial test rig successfully. Second, the rainflow matrices of strains on different proving ground roads are established and transformed into damage matrices based on the S-N curve and Miner rules using a reduction method. A standard simulation test for vehicle reliability procedure is established according to the proving ground schedule as a target to be accelerated.

Energy saving is becoming one of the most important issues for the next generation of commercial vehicles. The fuel consumption limits for commercial vehicles in China have stepped into the third stage, which is a great challenge for heavy duty commercial vehicles. Hybrid technology provides a promising method to solve this problem, of which the dual motor coaxial series parallel configuration is one of the best options. Compared with parallel configuration, the powertrain can not only operate in pure electric or parallel mode, but also can operate in series mode, which shows better flexibility. In this paper, regulations on test cycle, fuel consumption limits and calculation method of the third stage will be introduced in detail. Then, the quasi-static models of the coaxial series parallel powertrain with/without gearbox under C-WTVC (China worldwide transient vehicle cycle) are built. The control strategies are designed based on engine and motor performance.

Power-split configuration is highlighted as the most popular concept for full hybrid electric vehicles (HEV). However, the energy management and design of power-split heavy duty truck under Chinese driving conditions still need to be investigated. In this paper, the parametric design, a rule-based control strategy and an equivalent consumption minimization strategy (ECMS) for the power-split heavy duty truck are presented. Besides, the influence of a penalty factor also discussed under ECMS algorithm. Meanwhile, two different methods to search the engine operation point have been proposed and the reason of different economy performance is presented by using energy flow chart. And the simulation results show both fuel consumption can satisfy the second phase fuel consumption standard and the third phase fuel consumption standard which will be implemented in 2020, under C-WTVC (Chinese-World Transient Vehicle Cycle).

In this paper, gear ratios of a two-speed transmission system are optimized for an electric passenger car. Quasi static system models, including the vehicle model, the motor, the battery, the transmission system, and drive cycles are established in MATLAB/Simulink at first. Specifically, since the regenerative braking capability of the motor is affected by the SoC of battery and motors torque limitation in real time, the dynamical variation of the regenerative brake efficiency is considered in this study. To obtain the optimal gear ratios, iterations are carried out through Nelder-Mead algorithm under constraints in MATLAB/Simulink. During the optimization process, the motor efficiency is observed along with the drive cycle, and the gear shift strategy is determined based on the vehicle velocity and acceleration demand. Simulation results show that the electric motor works in a relative high efficiency range during the whole drive cycle.

Hybrid electric vehicles (HEV) are essential for reducing fuel consumption and emissions. However, when analyzing different segments of the transportation industry, for example, public transportation or different sizes of delivery trucks and how the HEV are used, it is clear that one powertrain may not be optimal in all situations. Choosing a hybrid powertrain architecture and proper component sizes for different applications is an important task to find the optimal trade-off between fuel economy, drivability, and vehicle cost. However, exploring and evaluating all possible architectures and component sizes is a time-consuming task. A search algorithm, using Gaussian Processes, is proposed that simultaneously explores multiple architecture options, to identify the Pareto-optimal solutions.

In vehicle accident, the bumper beam generally requires high stiffness for sufficient survival space for occupants while it may cause serious pedestrian lower extremity injuries. The aim of this study is to promote an aluminum-steel hybrid material double-hat bumper to meet the comprehensive requirements. The hybrid bumper is designed to improve the frontal crash and pedestrian protection performances in collision accidents. Finite element (FE) models of the hybrid bumper was built, validated, and integrated into an automotive model. The Fixed Deformable Barrier (FDB) and Transport Research Laboratory (TRL) legform model were used to obtain the vehicle crashworthiness and pedestrian lower leg injury indicators. Numerical results showed that the hybrid bumper had a great potential for crashworthiness performance and pedestrian protection characteristics. Based on this, a multi-objective optimization design (MOD) was performed to search the optimal geometric parameters.

This paper proposed a path coordination strategy for autonomous parking based on independently designed parking lot topological map. The strategy merges two types of paths at the three stages of path planning, to determinate mode switching timing between low-speed automated driving and automated parking. Firstly, based on the principle that parking spaces should be parallel or vertical to a corresponding path, a topological parking lot map is designed by using the point cloud data collected by LiDAR sensor. This map is consist of road node coordinates, adjacent matrix and parking space information. Secondly, the direction and lateral distance of the parking space to the last node of global path are used to decide parking type and direction at parking planning stage. Finally, the parking space node is used to connect global path and parking path at path coordination stage.

In recent years, the tractor-semitrailer combination has become the primary vehicle of China's long-distance freight system. In this paper, with the aim of optimizing the path tracking control and following control of the tractor-semitrailer combination, a kinematics-based path tracking control scheme is proposed. Firstly, a kinematic model of the tractor-semitrailer combination has been constructed. The control of the tractor-semitrailer combination is simplified to focus on three control points based on the kinematics model. Secondly, the path tracking control algorithm and the following control algorithm of the tractor-semitrailer combination are proposed in this paper. The improved MPC is used for path-tracking control of tractor-semitrailer combinations. The cost function of rolling optimization steps is intended, and the optimal line is determined with the lateral deviation, the variation of lateral error, and the deviation of heading angle as the input.

To further explore the potential of fuel economy for hybrid electric vehicle (HEV), a methodology of demand power optimization is proposed. The fuel consumption depends not only on the EMS, but also on the way to operate vehicle. A control strategy to adjust driver’s demand before power splitting is necessary. To get accurate and reliable control strategy, two aspects are the most important. First, a rigorous and organized modeling approach is a base to describe complicated powertrain system of HEV. The energetic macroscopic representation (EMR) is a graphical synthetic description of electromechanical conversion system based on energy flow. A powertrain architecture of HEV is described explicitly via the EMR. Second, the effectiveness of EMS and the reasonability of driving operations are vital.

Injection rate control is considered as an effective way to optimize diesel combustion process, decrease emission and improve fuel economy. There are many injection rate shaping devices, but most of them still suffer from structure complexity and parameter sensitivity which limit their effectiveness and practicality. A new initial injection rate control method in solenoid-controlled diesel injection systems is introduced in this paper. The basic idea of this method is to maintain a small spill passage between plunger chamber and inlet port during initial injection period. The initial injection rate can be regulated by changing the closing timing of the solenoid-controlled spill valve. This method has the advantages of simple construction, flexible adjustment and stable performance. Computer aided analysis and design based on a simulation program of the system is conducted to compare and select the sizes of the small spill passage according to their effect on injection characteristics.

Due to the potential on decreasing fuel consumption and design flexibility, parallel configurations are widely used for hybrid electric vehicles (HEVs). However, the fuel economy and economic profitability of parallel HEVs for heavy-duty truck applications under Chinese driving conditions still need to be investigated. It is uneasy to improve the fuel economy of parallel HEVs with a single electric motor from control perspective only. In this article, the battery size of the architecture is optimized by using the dynamic programming (DP) approach, based on a dynamic degradation model of the LiFePO4 battery. Moreover, based on the DP results, a near-optimal control strategy of the hybrid powertrain system for online application is proposed. Finally, with two economic assumptions, the initial costs, operation costs, and payback periods are obtained in a total cost of ownership framework perspective.

Multibody human models are widely used to investigate responses of human during an automotive crash. This study aimed to validate a commercially available multibody human body model against response corridors from volunteer tests conducted by Naval BioDynamics Laboratory (NBDL). The neck model consisted of seven vertebral bodies, and two adjacent bodies were connected by three orthogonal linear springs and dampers and three orthogonal rotational springs and dampers. The stiffness and damping characteristics were scaled up or down to improve the biofidelity of the neck model against NBDL volunteer test data because those characteristics were encrypted due to confidentiality. First, sensitivity analysis was performed to find influential scaling factors among the entire set using a design of experiment.

Both the economy and energy demand increase rapidly in China. The government is facing severe problems from energy security, carbon emissions and environmental issues. The past trends and future plans of energy will have great influence on the transportation, construction and industry development. This paper summarizes the present and future energy structure in China. Conventional fossil energy, nuclear energy and renewable energy are all included. Electricity will account for more proportion in total energy consumption in the future, and the structure of electricity will be cleaner. That will promote the development of electric vehicles and the transformation of China’s automotive industry. The optimization of energy structure will accelerate the low-carbon development in China. China’s energy development will enter a new stage from the expansion of total quantity to the upgrading of quality and efficiency.

The earth's fossil energy is not limitless, and we should be taking advantage of the highly developed fields of science and technology to utilize it more efficiently and to create a fully environmentally friendly life. Considering the prodigious amount of vehicles in the world today, even a small improvement in their energy-saving performance could have a significant impact. In this paper, a new type of electro-hydraulic power steering (EHPS) system is described. It has two main advantages. First, it can significantly decrease the demand on the motor so that it can be used for a wider range of vehicles. Second, its pressure-flow characteristic can be programmed and is more flexible than hydraulic power steering (HPS) system. A prototype with a 500 W motor was applied to a truck with a front load of 2,700 kg, and static steer sweep tests were conducted to validate its feasibility.