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Gas distribution of proton exchange membrane fuel cells (PEMFCs) is mainly decided by flow field of bipolar plate. The improper design of distributing channel, nonuniform gas flow distribution and current density distribution among different straight channels are the leading factors that could tremendously undermine the performance and life expectancy of the cell. However, there is lack of research focusing on distributing channel in straight-parallel flow field. In this work, a three-dimensional numerical model of PEMFC cathode flow field is developed with CFD method to investigate the effects of configuration type and width of the distributing channel on pressure distribution in distributing channel and on reactant flow distribution, pressure drop and concentration distribution in multiple straight channel. Effects of electrochemical reaction and formation of water on the flow distribution are taken into consideration.

Based on the working model of a diesel engine, the influence of 2 Miller cycle strategies-Early Intake Valve Closure (EIVC) and Late Intake Valve Closure (LIVC) on the combustion and emissions of diesel engine was analyzed. Then the working condition of each Miller cycle strategies on the engine under the rated speed was optimized through the adjust of the valve timing, boost pressure and the injection timing. The research found that both delaying and advancing the closure timing of the intake valve can decrease the pressure and temperature during compression stroke, prolonging the ignition delay. However, due to the decrease of the working media inside the cylinder, the average in-cylinder temperature and soot emissions will increase, which can be alleviated by raising the boost pressure and the resulting compensation of the intake loss.

Tracking vehicle trajectories is essential for autonomous vehicles and advanced driver-assistance systems to understand traffic environment and evaluate collision risk. In order to reduce the position deviation and fluctuation of tracking on-road vehicle by millimeter-wave radar (MMWR), an interactive multi-model Kalman filter (IMM-KF) tracking algorithm including data association and track management is proposed. In general, it is difficult to model the target vehicle accurately due to lack of vehicle kinematics parameters, like wheel base, uncertainty of driving behavior and limitation of sensor’s field of view. To handle the uncertainty problem, an interacting multiple model (IMM) approach using Kalman filters is employed to estimate multitarget’s states. Then the compensation of radar ego motion is achieved, since the original measurement is under the radar polar coordinate system.

Recently, electro-hydraulic brake systems (EHB) has been developed to take place of the vacuum booster, having the advantage of faster pressure build-up and continuous pressure regulation. In contrast to the vacuum booster, the pressure estimation for EHB is worth to be studied due to its abundant resource (i.e. electric motor) and cost-effective benefit. This work improves an interconnected pressure estimation algorithm (IPEA) based on actuator characteristics by introducing the vehicle dynamics and validates it via vehicle tests. Considering the previous IPEA as the prior pressure estimation, the wheel speed feedback is used for modification via a proportional-integral (PI) observer. Superior to the IPEA based on actuator characteristics, the proposed PEA improves the accuracy by more than 20% under the mismatch of pressure-position relation.

With the increasing worldwide concern on environmental pollution, battery electrical vehicles (BEV) have attracted a lot attention. However, it still couldn’t satisfy the market requirements because of the low battery power density, high cost and long charging time. The range-extended electrical vehicle (REEV) got more attention because it could avoid the mileage anxiety of the BEVs with lower cost and potentially higher efficiency. When internal combustion engine (ICE) works as the power source of range extender (RE) for REEV, its NVH, emissions in starting process need to be optimized. In this paper, a 2-cylinder PFI gasoline engine and a permanent magnet synchronous motor (PMSM) are coaxially connected. Meanwhile, batteries and load systems were equipped. The RE co-control system was developed based on Compact RIO (Compact Reconfigurable IO), Labview and motor control unit (MCU).

For an electric vehicle driven by four in-wheel motors, the torque of each wheel can be controlled precisely and independently. A closed-loop control method of differential drive assisted steering (DDAS) has been proposed to improve vehicle steering properties based on those advantages. With consideration of acceleration requirement, a three dimensional characteristic curve that indicates the relation between torque and angle of the steering wheel at different vehicle speeds was designed as a basis of the control system. In order to deal with the saturation of motor's output torque under certain conditions, an anti-windup PI control algorithm was designed. Simulations and vehicle tests, including pivot steering test, lemniscate test and central steering test were carried out to verify the performance of the DDAS in steering portability and road feeling.

Real-time interaction between a driver and the simulator is problematic. In this study, the racing car driving simulator has been established, which is composed of the following functional components: Motion Controller, Simview, Scenario Editor, Application Programmer Interface (APIs) and Crash Simulation. With TCP/IP protocol, the Motion Controller receives driver's manipulation, road unevenness and crash situation of Simview, then generates motion streams that reflecting the current conditions, and sends them to Simview and to the hydraulic platform. Furthermore, by detecting and analyzing general vehicle two-dimensional impact, a kind of complete and applicable calculation method has been established, and complicated vehicle impacts can be analyzed accurately. This racecar driving simulator places a racing driver in a interactive environment, and provides the driver with high-fidelity motion, visual, auditory, and force feedback cues.

Biomechanics and biodynamics are increasingly focused on the automotive industry to provide comfortable driving environment, reduce driver fatigue, and improve passenger safety. Man-centered conception is a growing emphasis on the open design of automobile. During the long-term driving, occupational drivers are easily exposed to the neck pain, so it is important to reduce the muscle force load and its fatigue, which are not usually considered quantitatively during traditional ergonomics design, so standards related are not well developed to guide the vehicle design; On the other hand, the head-neck models are always built based on the statics theory, these are not sufficient to predict the instantaneous variation of the muscle force. In this paper, a head-neck model with multi DOFs is created based on multibody dynamics. Firstly, a driver-vehicle-road model considering driver multi-rigid body model, vehicle subsystems, and different ranks of pavement is built.

Beamforming techniques are widely used today in aeroacoustic wind tunnels to identify wind noise sources generated by interaction between incoming flow and the test object. In this study, a planar spiral microphone array with 120 channels was set out-of-flow at 1:1 aeroacoustic wind tunnel of Shanghai Automotive Wind Tunnel Center (SAWTC) to test exterior wind noise sources of a production car. Simultaneously, 2 reference microphones were set in vehicle interior to record potential sound source signal near the left side view mirror triangle and the signal of driver’s ear position synchronously. In addition, a spherical array with 48 channels was set inside the vehicle to identify interior noise sources synchronously as well. With different correlation methods and an advanced algorithm CLEAN-SC, the ranking of contributions of vehicle exterior wind noise sources to interested interior noise locations was accomplished.

With the development of automotive HMI and mobile internet, many interactive modes are available for drivers to fulfill the in-vehicle secondary tasks, e.g. dialing, volume adjustment, music playing. For driving safety and drivers’ high expectation for HMI, it is urgent to effectively evaluate interactive mode with good efficiency, safety and good user experience for each secondary tasks, e.g. steering wheel buttons, voice control. This study uses a static driving simulation cockpit to provide driving environment, and sets up a high-fidelity driving cockpit based on OKTAL SacnerStudio and three-dimensional modeling technology. The secondary tasks supported by HMI platform are designed by customer demands research. The secondary task test is carried out based on usability test theory, and the influence on driving safety by different interactive modes is analyzed.

Based on the emergency lane change cases extracted from the China naturalistic driving data, the driving steering behavior divides into three phases: collision avoidance, lateral movement and steering stabilization. Using the steering primitive fitting by Gaussian function, the distribution of the duration time, the relationship between steering wheel rate and deflection were analyzed in three phases. It is shown that the steering behavior essentially is composed of steering primitives during the emergency lane-change. However, the combination of the steering primitives is different according to the specific steering constraints in three phases. In the collision avoidance phase, a single steering primitive with high peak is used for the fast steering; in the lateral movement and stabilization phase, a combination of two or even more steering primitives is built to a more accurate steering.

Driving posture study is essential for the evaluation of the occupant packaging. This paper presents a method of reconstructing driver’s postures in a real vehicle using a 3D laser scanner and Human Builder (HB), the digital human modeling tool under CATIA. The scanning data was at first converted into the format readable by CATIA, and then a personalized HB manikin was generated mainly using stature, sitting height and weight. Its pelvis position and joint angles were manually adjusted so as to match the manikin with the scan envelop. If needed, a fine adjustment of some anthropometric dimensions was also preceded. Finally the personalized manikin was put in the vehicle coordinate system, and joint angels and joint positions were extracted for further analysis.

X-in-the-loop (XiL) framework is a validation concept for vehicle product development, which integrates different virtual and physical components to improve the development efficiency. In order to develop and validate an extended validation method based on XiL, Tongji University in Shanghai, China and the Karlsruhe Institute of Technology (KIT) in Karlsruhe, Germany co- performed a feasibility study about an X-in-the-distance-loop demonstration platform. The X-in-the-distance-loop demonstration platform includes a MATLAB/Simulink software platform and geographically distributed equipment (driver simulator, driving electric motor and dynamometer test stand), which are used to conduct bidirectional experiments to test communication of powertrain data between China and Germany.

In the recent years, the interaction between human driver and Advanced Driver Assistance System (ADAS) has gradually aroused people’s concern. As a result, the concept of personalized ADAS is being put forward. As an important system of ADAS, Lane Keeping Assistance System (LKAS) also attracts great attention. To achieve personalized LKAS, driver lane keeping characteristic (DLKC) indices which could distinguish different driver lane keeping behavior should be researched. However, there are few researches on DLKC indices for personalized LKAS. Although there are many researches on modeling driver steering behavior, these researches are not sufficient to obtain DLKC indices. One reason is that most of researches are for double lane change behavior which is different from driver lane keeping behavior. The other reason is that the researches on driver lane keeping behavior only provide model structure and rarely discuss identification procedure such as how to select suitable data.

In order to investigate the impacts of recirculated exhaust gas temperature on gasoline engine combustion and emissions, an experimental study has been conducted on a turbocharged PFI gasoline engine. The engine was equipped with a high pressure cooled EGR system, in which different EGR temperatures were realized by using different EGR coolants. The engine ran at 2000 r/min and 3000 r/min, and the BMEP varied from 0.2MPa to 1.0MPa with the step of 0.2MPa. At each case, there were three conditions: 0% EGR, 10% LT-EGR, 10% HT-EGR. The results indicated that LT-EGR had a longer combustion duration compared with HT-EGR. When BMEP was 1.0 MPa, CA50 of HT-EGR advanced about 5oCA. However, CA50 of LT-EGR could still keep steady and in appropriate range, which guaranteed good combustion efficiency. Besides, LT-EGR had lower exhaust gas temperature, which could help to suppress knock. And its lower exhaust gas temperature could reduce heat loss. These contributed to fuel consumption reduction.

Biodiesel as a renewable energy is becoming increasingly attractive due to the growing scarcity of conventional fossil fuels. Meanwhile, the development of after-treatment technologies for the diesel engine brings new insight concerning emissions especially the particulate matter pollutants. In order to study the coupling effects of biodiesel blend and CCRT (Catalyzed Continuously Regeneration Trap) on the particulate matter emissions, the particulate matter emissions from an urban bus with and without CCRT burning BD0 and BD10 respectively was tested and analyzed using electrical low pressure impactor (ELPI). The operation conditions included steady state conditions and transient conditions. Results showed that the particulate number-size distribution of BD10 and BD0 both had two peaks in nuclei mode and accumulation mode at the conditions of idle, low speed and medium speed while at high speed condition the particulate number-size distribution only had one peak.

In China there are many mixed driving roads which cause a lot of safety problems between vehicles and pedalcyclists. Research on driver behavior under risk scenarios with pedalcyclist is relatively few. In this paper driver brake parameters under naturalistic driving are studied and pedalcyclists include bicyclist, tricyclist, electric bicyclist and motorcyclist. Brake reaction time and maximum brake jerk are used to evaluate driver brake reaction speed. Average deceleration is used to evaluate the effect of driver brake operation. Maximum deceleration is used to evaluate driver braking ability. Driver behaviors collected in China are classified and risk scenarios with pedalcyclist are obtained. Driver brake parameters are extracted and statistical characteristics of driver brake parameters are obtained. Influence factors are analyzed with univariate ANOVA and regression analysis.

Due to much higher pressure and pressure rising rate, knocking is always of potential hazards causing damages in the engine and high NOX emissions. Therefore, the researchers have focused on knocking diagnosis and control for many years. However, there is still lack of fast response sensor detecting in-cycle knocking. Until now, the feedback control based on knocking sensor normally adjusts the injection and ignition parameters of the following cycles after knocking appears. Thus in-cycle knocking feedback control which requires a predictive combustion signal is still hard to see. Ion current signal is feasible for real-time in-cylinder combustion detection, and can be employed for misfiring and knocking detection. Based on incylinder pressure and ion current signals, the in-cycle knocking feedback control is investigated in this research. The 2nd-order differential of in-cylinder pressure, which means the response time of pressure rising rate dPR, is employed for knocking prediction.

With regulatory standards for diesel engine emissions becoming stricter worldwide, integrated catalytic systems are becoming increasingly necessary. One of the better approaches is to use an after-treatment system consisting of a diesel oxidation catalyst (DOC), a catalyzed diesel particulate filter (CDPF), and a selective catalytic reduction (SCR), but many factors can affect how well this system works. This study investigates the effects of DOC and CDPF catalyst composition on emissions characteristics for DOC + CDPF + SCR systems by collecting reactor and engine data. The reactor results show that the light-off temperatures (T50) of CO and C3H6 increase with the growth of Pt:Pd ratio while the T50 of NO degrades. An engine dynamometer test was conducted on a light-duty diesel engine equipped with DOC + CDPF + SCR. The results show light-off curves of CO and THC that are smoother than the reactor data.

With the introduction of BroadR-Reach and time-sensitive networking (TSN), Ethernet has become an option for in-vehicle networks (IVNs). Although it has been used in the IT field for decades, it is a new technology for automotive, and thus requires extensive testing. Current test solutions usually target specifications rather than the in-vehicle environment, which means that some properties are still uncertain for in-vehicle usage (e.g., fault tolerance for shorted or open wires). However, these characteristics must be cleared before applying Ethernet in IVNs, because of stringent vehicular safety requirements. Because CAN is usually used for these environments, automotive Ethernet is expected to have the same or better level of fault tolerance. Both CAN and BroadR-Reach use a single pair of twisted wires for physical media; thus, the traditional fault-tolerance test method can be applied for automotive Ethernet.