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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.

The convolutional neural network (CNN) has achieved extraordinary performance in image classification. However, the implementation of such architecture on embedded platforms is a big challenge task due to the computing resource constraint issue. This paper concentrates on optimization of CNN on embedded platforms with a case study of pedestrian detection in ADAS. The main contribution of this proposed CNN is its ability to run pedestrian classification task in real time with high accuracy based on a platform with ARM embedded. The CNN model has been trained with GPU locally and then transformed into an efficient implementation on embedded platforms. The efficient implementation uses dramatically small network scale and a lightweight CNN is obtained. Specifically, parameters of the network are compressed by adopting integer weights to reduce computational complexity. Meanwhile, other optimizations have also been proposed to adapt the general ARM processor architecture.

Two-stroke engines have to face the problems of insufficient charge for short intake time and the loss of intake air caused by long valve overlap. In order to promote the power of a two-stroke poppet valve diesel engine, measures are taken to help optimize intake port structure. In this work, the scavenging and combustion processes of three common types of intake ports including horizontal intake port (HIP), combined swirl intake port (CSIP) and reversed tumble intake port (RTIP) were studied and their characteristics are summarized based on three-dimensional simulation. Results show that the RTIP has better performance in scavenging process for larger intake air trapped in the cylinder. Its scavenging efficiency reaches 84.7%, which is 1.7% higher than the HIP and the trapping ratio of the RTIP reaches 72.3% due to less short-circuiting loss, 11.2% higher than the HIP.

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.

In automatic driving application, the velocity planner can be considered as a key factor to ensure the safety and comfort. One of the most important tasks of the velocity planner is to simulate the velocity characteristics of human drivers. In this paper, two Driver In-the-Loop (DIL) experiments are designed to explain velocity characteristics of human drivers. In the first experiment, static obstacles are placed on both sides of the straight road to shorten the cross range that vehicles can driver across. Moreover, different cross ranges are set to study the influence of the steering wheel error. In the second experiment, velocity characteristics are investigated under the condition of different road widths and curvatures in a U-turn road contour. In both tests, different drivers’ preview behavior is analyzed through the operation of throttle, braking, and steering.

The performance of a commercial Cu-zeolite SCR catalyst after differing degrees of hydrothermal aging (aged for 72 hours at 500, 700 and 800°C with 10% moisture balanced with air) was studied by spatially resolving different key reactions using gas-phase FTIR measurements. Gases were sampled along a channel at different positions and analyzed using FTIR, which overcomes the interference of water and nitrogen on ammonia concentration detection encountered in standard mass spectrometer-based spatial resolution measurements. The NO:NO₂ concentration ratio was changed so that the standard (NO:NO₂ = 1:0), fast (NO:NO₂ = 1:1) and NO₂ (NO:NO₂ = 0:1) SCR reactions could be investigated as a function of the catalyst's hydrothermal aging extent. In addition, the effects of hydrothermal aging on the activity of NH₃ and NO oxidation were also investigated. Hydrothermal aging had little effect on NO oxidation activity.

Vehicle needs suspension and steering systems with different features to fit different driving conditions. In normal straight driving condition, soft suspension and heavy steering systems are needed to achieve better ride comfort and straight line driving stability; in turning conditions, hard suspension and lightweight steering systems are needed to get better handing stability. The semi-active suspension system with Magneto-Rheological dampers can improve the ride comfort and handling performance of vehicle. Electrical power steering system is developed rapidly due to its portable and flexible operations as well as stable steering performance.

Lean-burn Spark Ignition Direct Injection (SIDI) engines offer potential fuel economy savings, however, lack of cost-effective lean NOx aftertreatment systems has hindered its broad application. Lean NO Trap (LNT) and Urea Selective Catalytic Reduction (SCR) technologies have been widely investigated as possible solutions, but they both have considerable drawbacks. LNT catalysts suffer from high Platinum Group Metals (PGM) cost, poor thermal durability, sulfur poisoning and active SO regeneration requirements. Urea SCR systems require a secondary fluid tank with an injection system, resulting in added system cost and complexity. Other concerns for urea SCR include potential freezing of the urea solution and the need for customers to periodically fill the urea reservoir. In this paper we report a low-cost, high efficiency concept that has the potential to be a key enabler for lean-burn gasoline engines.

An electronic controlled rapid burning system with a high energy, dual-spark plug ignition system in a high speed LPG engine with a sole LPG-fueled port fuel injection (PFI) system for the steady state lean operation is discussed in this paper. A Multi-channel SI engine Combustion Process Analysis System was developed in this research. The synchronizing and asynchronous ignition timing can be realized by ECU and the control strategies according to the engine operation conditions. Test results showed that the lean mixture flame propagation was improved by the enhanced ignition energy intensity in this system. To cooperate with the combustion chamber and the spark location, the flame propagation distance was shortened for rapid burning.

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.

The energy storage system (ESS) is the key enabler to hybrid electric vehicles (HEVs) that offer improved fuel economy and reduced vehicle emissions. The power capability of a battery has significant impact on the fuel economy of HEVs. This paper presents the power capability testing of a lithium-ion battery with a conventional metal oxide cathode using the hardware in the loop (HIL) at a wide range of charge/discharge conditions and at different temperatures. The achieved test results provide critical data of battery power characteristics and effectively accelerate the development of battery power prediction algorithm.

A novel urea evaporation and mixing device has been developed to improve the overall performance of a urea-SCR system. The device was tested with a MY2007 Cummins ISB 6.7L diesel engine equipped with an SCR aftertreatment system. Test results show that the device effectively improved the overall NO conversion efficiency of the SCR catalyst over both steady-state and transient engine operating conditions, while NH₃ slip from the catalyst decreased.

In heavy truck driveline system, the components often include clutch, transmission, transfer case, drive shaft, etc. A fluid torque converter could be equipped in front of the transmission in order to improve the starting performance. Meanwhile, a hydraulic retarder could be introduced for auxiliary braking so as to adapt the truck to the brake on long downgrade in mountainous regions. Thus, the driveline heat load would have a notable increase. Both the fluid torque converter and the hydraulic retarder would produce a large quantity of heat, and a special cooling system is needed for adjusting the transmission fluid temperature with which the gains are potentially very large [1]. The heat load for driveline is often calculated based on empirical formula. For the heavy truck, however, if the heat value is underestimated, driveline components would suffer from overheated damage.

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.

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.

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.

As vehicle fuel economy requirements continue to increase it is becoming more challenging and expensive to simultaneously improve fuel consumption and meet emissions regulations. The Passive Ammonia SCR System (PASS) is a novel aftertreatment concept which has the potential to address NOx emissions with application to both lean SI and stoichiometric SI engines. PASS relies on an underfloor (U/F) SCR for storage of ammonia which is generated by the close-coupled (CC) TWCs. For lean SI engines, it is required to operate with occasional rich pulses in order to generate the ammonia, while for stoichiometric application ammonia is passively generated through the toggling of air/fuel ratio. PASS serves as an efficient and cost-effective enhancement to standard aftertreatment systems. For this study, the PASS concept was demonstrated first using lab reactor results which highlight the oxygen tolerance and temperature requirements of the SCR.

Lean-burn SIDI engine technology offers improved fuel economy; however, the reduction of NOx during lean-operation continues to be a major technical hurdle in the implementation of energy efficient technology. There are several aftertreatment technologies, including the lean NOx trap and active urea SCR, which have been widely considered, but they all suffer from high material cost and require customer intervention to fill the urea solution. Recently reported passive NH₃-SCR system - a simple, low-cost, and urea-free system - has the potential to enable the implementation of lean-burn gasoline engines. Key components in the passive NH₃-SCR aftertreatment system include a close-coupled TWC and underfloor SCR technology. NH₃ is formed on the TWC with short pulses of rich engine operation and the NH₃ is then stored on the underfloor SCR catalysts.

In this paper, a Magneto-Rheological (MR) fluid semi-active suspension system was tested on a commercial vehicle, a domestic light bus, to determine the performance improvements compared to passive suspensions. MR fluid is a material that responds to an applied magnetic field with a significant change in its rheological behavior. When the magnetic field is applied, the properties of such a fluid can change from a free-flowing, low viscosity fluid to a near solid, and this change in properties takes place in a few milliseconds and is fully reversible. A quarter suspension test rig was built out to test the nonlinear performance of MR damper. Based on a large number of experimental data, a phenomenological model of MR damper based on the Bouc-Wen hysteresis model was adopted to predict both the force-displacement behavior and the complex nonlinear force-velocity response.

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.