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This work analyzes the transmission efficiency of vehicle driveline including the gearbox, universal transmission and differential. Based on the structure of transmission, mathematic models are built to analyze transmission's characteristics. However, an experiment reveals the limitation of this method. Then, the paper statistically analyzes the experimental data and mainly analyzes the influencing factors. Then Neural Network is used to build the efficiency model. A method called “filling data and gradually extrapolating” is used when building neural network model. Finally, the neural network model is used in the simulation of fuel consumption. The conclusion is Neural Network model can imitate the transmission efficiency of vehicle driveline efficiently, but its internal structure is not clear so other modeling methods are needed to be found.

The hydraulic retarder is the most stabilized auxiliary braking system [1-2] of heavy-duty vehicles. When the hydraulic retarder is working during auxiliary braking, all of the braking energy is transferred into the thermal energy of the transmission medium of the working wheel. Theoretically, the residual heat-sinking capability of the engine could be used to cool down the transmission medium of the hydraulic retarder, in order to ensure the proper functioning of the hydraulic retarder. Never the less, the hydraulic retarder is always placed at the tailing head of the gearbox, far from the engine, long cooling circuits, which increases the risky leakage risk of the transmission medium. What's more, the development trend of heavy load and high speed vehicle directs the significant increase in the thermal load of the hydraulic retarder, which even higher than the engine power.

Hydraulic retarder has been widely applied on military vehicles and heavy commercial vehicles because of it could provide great brake torque and has lasting working time [1]. In order to reduce driver's frequent actions in braking process and prevent hydraulic retarder system from overheating, it is need to apply constant braking torque control, this control target has a strict requirement to hydraulic control system design. Many parameters often require repeated test to determine, which increases the R&D cost and extends the research cycle. This paper tries to find a time-efficient research method of hydraulic retarder control system through studying on a heavy military vehicle hydraulic retarder system. Hydraulic retarder model is set up through test data. The hydraulic control system is built based on AMESim. Controller model is set up based on PID control. The whole vehicle brake model is built based on MATLAB/Simulink.

In order to perform differential control instead of the mechanical differential and improve the steering performance of distributed electric vehicles, a two-level differential speed steering control strategy is proposed. Firstly, an upper-layer controller to track the yaw rate is designed based on PID feedback and 3-D lookup table model, which could shorten the response time and reduce the impact of model parameters mismatch. Then, in order to improve the robustness to external disturbances and parameter uncertainties, a lower-layer controller to track the wheel speed is proposed based on integral sliding mode control. Moreover, three simulations are conducted to validate the proposed strategy. The first simulation results indicate that the driving torques of the inner and outer wheels are distributed properly to avoid wheel slip. In the second simulation, when the conventional steering system fails, the proposed control strategy could avoid vehicle losing steering function.

Path planning system, which is one of driver assistance systems, can calculate the driving paths and estimate the driving time through the road information provided by information source. Traditional path planning systems calculate the driving paths through Dijsktra's algorithm or A* algorithm but only consider the road information from electronic maps. It is not safe enough for operating vehicles because of the insufficient information of vehicle performance as well as the driver's willingness. This study is based on the Dijsktra's algorithm, which comprehensively considered vehicular active safety constraints such as road information, vehicle performance and the driver's willingness to optimize the Dijsktra's algorithm. Then the path planning system can calculate the optimal driving paths that would satisfy the safety requirement of the vehicle. This study used LabVIEW as a visual host computer and MATLAB to calculate dynamic property of the vehicle.

Dynamic modeling and state estimation are significant in the trajectory tracking and stability control of the intelligent vehicle. In order to meet the requirement of the stability control of the eight-in-wheel-motor-driven intelligent vehicle, a full vehicle dynamics model with 12 degrees of freedom, including the longitudinal, lateral, yaw and roll motion of the body, and rotational motion of 8 wheels, is established for the research of the intelligent vehicle in this paper. By simulation with MATLAB/SIMULINK and by comparison with the TruckSim software, the reliability and practicality of the dynamics model are verified. Based on the established dynamics model, an extended Kalman filter (EKF) state observer is proposed to estimate the vehicle sideslip angle, roll angle and yaw rate, which are the key parameters to the stability control of the intelligent vehicle.

The hydraulic retarder used in commercial vehicles can provide hydraulic damping to generate braking torque, reducing the pressure of the braking system on the slope section and increasing the safety. In this paper, the magnetorheological fluid with fast magnetic field reflection characteristics is used to increase the response speed of the hydraulic retarder, which can effectively reduce the response time of the hydraulic retarder. In this paper, the influence of the change of circumferential magnetic field on the braking torque of the magnetorheological fluid retarder is studied.

The paper studies on the basis of VOITH R133-2 hydraulic retarder, the inlet and outlet structures of the oil passage on the stator are rearranged, which are made a more uniform structure distribution. In order to find out the characteristics of this kind of structure arrangement. The flow passage models for two different structures are established, and the internal flow field characteristics are studied by using the CFD (Computational Fluid Dynamics) method. The flow rules of the internal oil, the distribution of pressure field and velocity field as well as output braking torque are obtained. The results show that rearranged structure retarder has a more uniform pressure distribution and a lower output braking torque than original structure retarder. And the simulation verifies the effectiveness of simulating true flow by CFD in hydraulic retarder flow field and conduct retarder design and structure optimization.

Vehicle hydraulic retarders are applied in heavy-duty trucks and buses as an auxiliary braking device. In traditional cooling systems of hydraulic retarders, the working fluid is introduced into the heat exchanger to transfer heat to the cooling liquid in circulation, whose heat is then dissipated by the engine cooling system. This prevents the waste heat of the working fluid from being used effectively. In hydraulic retarder cooling system based on the Organic Rankine Cycle, the organic working fluid first transfers heat with the hydraulic retarder working fluid in Rankine cycle, and then outputs power through expansion machine. It can both reduce heat load of the engine cooling system, and enhance thermal stability of the hydraulic retarder while recovering and utilizing braking energy. First of all, according to the target vehicle model, hydraulic retarder cooling system model based on Rankine cycle is established.

In the Rankine cycle, the pressure differential generated by the phase change of the working fluid produces turbine output power, which enables the recovery of waste heat from the internal combustion engine. The heat transfer ability of the evaporator is the key factor that determines the quality of turbine's mechanical work. In this paper, the performance of the evaporator with two-phase zone and preheated zone is studied. After obtaining the thermal characteristics of diesel engine exhaust from the experimental data, the mathematical model of the evaporator is built according to the specific working conditions of ORC and geometrical parameters of the evaporator. Three typical engine operating conditions are used to estimate the heat transfer characteristics of the evaporator. The result shows that, in the evaporator, the heat transfer coefficient of the Rankine working fluid is much greater than the exhaust side of the engine.

Semi-active suspension has been widely applied in commercial vehicle suspension in order to get good riding comfortableness. Fuzzy logic control (FLC) has been widely applied in the field of kinetic control because control rule of FLC is easy to understand. But the gain of fuzzy rules and adjustment of membership functions usually depend on experts' experiences and repeated experiments, thus the fuzzy rules and membership functions has strong subjectivity, also are easily affected by environment of experiments, so the main problem of fuzzy logic controller design is selection and optimization of fuzzy rules and membership functions. Genetic Algorithms (GA) is the algorithm that searches the optimal solution through simulating natural evolutionary process and is one of the evolution algorithms which have most extensive impact.

In this paper a new pressure control method of a modified accumulator-type Electro-hydraulic Braking System (EHB) is proposed. The system is composed of a hydraulic motor pump, an accumulator, an integrated master cylinder, a pedal feel simulator, valves and pipelines. Two pressurizing modes are switched between by-motor and by-accumulator to adapt different pressure boost demands. A differentiator filtering raw sensor signal and calculating pedal speed is designed. By using the pedal feel simulator, the relationship between wheel pressures and brake force is decoupled. The relationships among pedal displacement, pedal force and wheel pressure are calibrated by experiments. A model-based PI controller with predictor is designed to lower the influences caused by delay. Moreover, a self-tuning regulator is introduced to deal with the parameter’s time-varying caused by temperature, brake pads wearing and delay variation.

Brake pedal feel plays an important role in the driver's comprehensive subjective feeling when braking, which directly affects the active safety and riding comfort of passenger car. A systematical mathematical model of the vehicle brake system is built in according with the structure and system characteristics of hydraulic servo brake system. A complete hydraulic servo brake system simulation model composed of brake pedal, vacuum booster, brake master cylinder, brake pipe, brake wheel cylinders, brake calipers is established in AMESim. The effects of rubber reaction plate stiffness, rubber valve opening, brake master cylinder piston, brake caliper, brake pipe deformation and friction liner deformation on brake pedal feel are considered in this model. The accuracy of this model is verified by real road vehicle tests under static and dynamic two different conditions.

Blade Electric Vehicle (BEV) with a light body plays an important role in saving the energy and reducing the exhaust emission. However, reducing the body weight need to meet the heterogeneous attributes such as structural, safety and NVH (Noise, Vibration and Harshness) performance. With the rapid development of finite element (FE) analysis technology, simulation analysis is widely used for researching the complex engineering design problem. Multidisciplinary Design Optimization (MDO) of a BEV body is a challenging but meaningful task in the automotive lightweight. In present research, the MDO is introduced to optimize a BEV Body-in-White (BIW).

On road simulation, both the traditional iterative method based on frequency response function (FRF) and adaptive control method based on the CARMA model are realized by using linear model to identify the target test system. However the real test system is very complicated because of various nonlinear factors. Linear models approximately describe the system only in a small range. Therefore, system simulation methods can not be used to validate the developed control algorithm and the uncertainty of test accordingly increases. As mentioned above, this paper presents a model to identify the nonlinear test system using NARMA dynamic neural network and discusses how to make the model parameters in detail. Using the test input-output series data, this network was trained by Levenberg-Marquardt method. Results of verification simulation show the validation of the nonlinear model.

Focusing the vehicle riding safety and global environmental problems, plenty of solutions on vehicle braking systems appeals during the recent period. Criteria and standards set up for commercial vehicles which should have equipped assisted braking systems were established by amounts of governments. Since eddy current retarders plays an important role in the area of assisted braking system, this article presents an energy-recuperation retarder, which is parallel connected with the driveline through a planet gear system. This paper offers a particular Energy-Recuperation Eddy Current Retarder (ERECR) system with a pedal control system and its characteristics is presented, either. Initially, the constitution of the energy-recuperation eddy current retarder system is established whereas the working principle of the energy-recuperation eddy current retarder is presented by modeling the system and simulation.

The drivability plays an important role for marketability and competitiveness of passenger car in meeting some customer requirements, which directly affects the driving experience and the desire of purchasing. In this paper, a framework of objective drivability evaluation with multi-source information fusion for passenger car is proposed. At first, according to vehicle powertrain system and optimization theory, certain vehicle performances, which are closely related to objective drivability are analyzed, including vehicle longitudinal acceleration, vehicle speed, engine torque, engine speed, gear position, accelerator pedal, brake signal and voltage signal. Then, combined with the evaluation criterion of signal-to-noise ratio (SNR), mean error (ME), root mean squared error (RMSE) and signal smoothness (SS), a de-noising method is developed for the drivability evaluation information.

Road simulation experiment in laboratory is a most important method to enhance the design quality of vehicle products. Presently, two main control techniques for road simulation—remote parameter control (RPC) and minimum variance adaptive control—are both defective: the former becomes an open-loop control after generating the drive signals, however the latter is essentially a kind of gradual control. To realize the closed-loop control and increase the control quality, this article brings forward a PID open-closed loop control method. Firstly taking the original road simulator as a group to identify, a nonlinear autoregressive moving average (NARMA) model was built with the dynamic neural network. Subsequently, this plant model was used to build the open-closed loop control system mentioned above. In the closed-loop a discrete PID controller was introduced to stabilize the system, while a P-type iterative learning control (ILC) was adopted to increase the control quality.

Path tracking is one of the critical technologies in the autonomous vehicle. Its performance may be seriously affected by disturbance resulting from unpredictable environment like changes in road friction coefficient and parameter uncertainty such as cornering stiffness and mass caused by errors of measurement. Besides, since the vehicle system consisting of many systems is an extremely complex nonlinear system, it is almost impossible for us to establish a precise model of a vehicle especially when it is moving. These inevitable factors influence the control accuracy and even threaten the stability and safety of the vehicle system. This paper proposed a promising solution to this problem, robust MPC (Model Predictive Control) combined with the optimal preview controller for path tracking problems of an autonomous vehicle. The state space model in tracking error variables of a passenger vehicle used for path tracking application is established.

A vehicular hydraulic electrical energy regenerative semi-active suspension(HEERSS) was presented, and its working principle and performance were analyzed. Firstly, configuration and working principle of the HEERSS were described; Secondly, kinetic equation of HEERSS was deduced, and a skyhook controller was designed for HEERSS. The traditional skyhook control strategy should be changed for the characteristic of HEERSS, because the damping force during extension stroke could be controlled, but not in compression stroke. Thirdly, the performance of HEERSS was compared with passive suspension(PS), traditional semi-active suspension(TSS). The simulation results indicated that the performance of HEERSS would be compromise between TSS and PS, but the HEERSS could harvest vibration energy which was advanced than TSS and PS.