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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.

As one of the most crucial components in electric vehicles, power batteries generate abundant heat during charging and discharging processes. Thermal management system (TMS), which is designed to keep the battery cells within an optimum temperature range and to maintain an even temperature distribution from cell to cell, is vital for the high efficiency, long calendar life and reliable safety of these power batteries. With the desirable features of low system complexity, light weight, high energy efficiency and good battery thermal uniformity, thermal management using composite phase change materials (PCMs) has drawn great attention in the past fifteen years. In the hope of supplying helpful guidelines for the design of the PCM-based TMSs, this work begins with the summarization of the most commonly applied heat transfer enhancement methods (i.e., the use of thermally conductive particles, metal fin, expanded graphite matrix and metal foam) for PCMs by different researchers.

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.

Recent toxicological and epidemiologic studies have shown that diesel emissions have been a significant toxic air contaminant. Catalyzed DPF (CDPF) not only significantly reduces the PM mass emissions (>90%), but also further promotes carrier self-regeneration and oxidize more harmful gaseous pollutants by the catalyst coated on the carrier. However, some ultrafine particles and potentially harmful gaseous pollutants, such as VOCs species, originally emitted in the vapor-phase at high plume temperature, may penetrate through the CDPF filter. Furthermore, the components and content of catalyst coated on the CDPF could influence the physicochemical properties and toxicity intensity of those escaping ultrafine particles and gaseous pollutants. In this work, (1) we investigated the influence of precious metal content as a variable parameter on the physicochemical properties and catalytic activities of the small CDPF samples.

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.

Traditional active suspension which is equipped with hydraulic actuator or pneumatic actuator features slow response and high power consumption. However, electromagnetic actuated active suspension benefits quick response and energy harvesting from vibration at the same time. To design a novel active and energy regenerative suspension (AERS) utilizing electromagnetic actuator, this paper investigates the benchmark cars available on the market and summaries the suspension features. Basing on the investigation, a design reference for AERS design is proposed. To determine the parameters of the actuator, a principle is proposed and the parameters of the actuator are designed accordingly. Compared the linear type and rotary type Permanent Magnet Synchronous Motor (PMSM), the rotary type is selected to construct the actuator of the AERS. Basing on the suspension structure of the design reference model and utilizing rotary type PMSM, a novel AERS structure is proposed.

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.

By means of particle image velocimetry(PIV) measurements, this paper uses vortex identification algorithms to find and analyze the coherent structures in the shear layer region of a 1:15 scaled 3/4 open jet automotive wind tunnel with a high Reynolds number(about 106), referring to SAWTC’s AAWT. The proper orthogonal decomposition(POD) is used to process the PIV experimental data to reconstruct the velocity fields. Based on the vortex identification functions, the locations of the center, the rotation direction and the radius of vortex can be computed. Furthermore, this paper uses the statistical method to study the regularities of distribution of these vortexes in a two-dimensional plane, and identify the vortex pairing process in the shear layer region. This paper also chooses different vortex identification algorithms to find the most accurate and suitable algorithms.

The integrated control system which combines the differential drive assisted steering (DDAS) and the direct yaw moment control (DYC) for the distributed drive electric vehicle (DDEV) is studied. A handling improvement algorithm for the normal cornering maneuvers is proposed based on motion tracking control. Considering the ideal assistant power character curves at different velocities, an open-loop DDAS control strategy is developed to respond the driver’s demand of steering wheel torque. The DYC strategy contains the steering angle feedforward and the yaw rate feedback. The steering angle feedforward control strategy is employed to improve yaw rate steady gain of vehicle. The maximum feedforward coefficients at different velocities are obtained from the constraint of the motor external characteristic, final feedforward coefficients are calculated according to the ideal assistant power character curve of the DDAS.

The maximum equivalent plastic strain (EPSmax), which can be achieved in the gauge region of a cruciform specimen during in-plane biaxial tensile tests, is limited due to early fracture on the cruciform specimen arm. In this paper, a theoretical model was proposed to determine the factors related to the EPSmax of a cruciform specimen following ISO 16842: 2014. Biaxial tensile tests were carried out to verify the theoretical analyses. Results show that the material strength coefficient (k) has no effect on the EPSmax, and EPSmax increases with the increase of the material hardening exponent (n) and the cross-sectional-area ratio (c) of the arm region to the gauge region. It is found that the applied load ratio (α) has an effect on EPSmax, which decreases as the load ratio increases from 0:1 (i.e. uniaxial tension) to 1:2 (i.e. plane strain state) and then increases as the load ratio increases to 1:1 (i.e. balanced biaxial tension).

The coordinated control of stability and steering systems in collision avoidance steering evasion has been widely studied in vehicle active safety area, but the studies are mainly aimed at autonomous vehicle without driver or conventional combustion engine vehicle. This paper focuses on the control of hybrid vehicle integrated with rear hub in emergency steering evasion situation, and considering the driver’s characteristics. First, the mathematics model of vehicle dynamics and driver has been given. Second, based on the planned steering evasion path, the model predictive control method is presented for achieving higher evasion path tracking accuracy under driver’s steering input. The prediction model includes an adaptive preview distance driver model and a vehicle dynamics model to predict the driver input and the vehicle trajectory.

Battery models are often applied to describe the dynamic characteristics of batteries and can be used to predict the state of the battery. Due to the process of charging and discharging, the battery heat generation will cause the inhomogeneity between inner battery temperature and surface temperature. In this paper, a novel battery impedance model, which takes the impact of the battery internal temperature gradient on battery impedance into account, is proposed to improve the battery model performance. Several experiments are designed and conducted for pouch typed battery to investigate the electrochemical impedance spectroscopy (EIS) characteristics with the artificial temperature gradient (using a heating plate). Experimental results indicate that the battery internal temperature gradient will influence battery EIS regularly.

As the connectivity of vehicles increases rapidly, more vehicles have the capability to communicate with each other. Because Vehicular Ad-hoc NETworks (VANETs) have the characteristics of solid mobility and decentralization, traditional security strategies such as authentication, firewall, and access control are difficult to play an influential role. As a soft security method, trust management can ensure the security attributes of VANETs. However, the rapid growth of newly encountered nodes of the trust management system also increases the requirements for trust establishing mechanisms. Without a proper trust establishment mechanism, the trust value of the newly encountered nodes will deviate significantly from its actual performance, and the trust management system will suffer from newcomer attacks.

The conventional crash box with thin-walled column conceals some limitations on pedestrian protection and lightweight. The metallic NPR metamaterials designed in this study are based on re-entrant lattice structures. Re-entrant structures are known to be one main class of axenic structures that display negative Poisson’s ratio (NPR), which can be manufactured by 3D printing technology. This kind of metamaterial has good designability and can be used as the filling structure of the crash box to improve the crashworthiness of the car. This paper starts from the relations between geometric parameters of the metamaterial. Considering the deformation characteristics of the crash box, the structure were designed into some gradient types. The mechanical properties of different gradient structures under the same impact conditions were compared to find the proper gradient structures. Based on the studies, the gradient lattice structure is applied to the automobile crash box.

For a practical pad design, a magnetic shielding layer is imperative which is made of ferrite, aluminum or some other metallic material. However, once the magnetic shielding layer is added, not only the mutual inductance but also the self-inductance of the coupling coils vary with the lateral misalignment which is inevitable for a human driver. The change of self-inductance will also result in the mistuning problem in the resonant circuit, which can significantly reduce the transmission efficiency of the whole wireless power transfer (WPT) system. This paper proposed a method of parameter identification of self-inductance based on the least square in order to solve the mistuning problem. In order to verify the proposed method, both the simulation model and the experiment set-up are built.

Cut-in scenario is common in traffic and has potential collision risk. Human driver can detect other vehicle’s cut-in intention and take appropriate maneuvers to reduce collision risk. However, autonomous driving systems don’t have as good performance as human driver. Hence a deeper understanding on driving behavior is necessary. How to make decisions like human driver is an important problem for automated vehicles. In this paper, a method is proposed to classify the dangerous cut-in situations and normal ones. Dangerous cases were extracted automatically from naturalistic driving database using specific detection criteria. Among those cases, 70 valid dangerous cut-in cases were selected manually. The largest deceleration of subject vehicle is over 4 m/s2. Besides, 249 normal cut-in cases were extracted by going through video data of 2000km traveled distance. In normal driving cases, subject vehicle may brake or keep accelerating and the largest deceleration was less than 3 m/s2.

The past decade has witnessed the rapid development of autonomous parking technology, since it has promising capacity to improve traffic efficiency and reduce the burden on drivers. However, it is prone to the trap of self-centeredness when each vehicle is automated parking in isolation. And it is easy to cause traffic congestion and even chaos when multiple autonomous vehicles require of parking into the same lot. In order to address the multiple vehicle parking problem, we propose a parking planning method with genetic algorithm. Firstly, an optimal mathematic model is established to describe the multiple autonomous vehicle parking problem. Secondly, a genetic algorithm is designed to solve the optimization problem. Thirdly, illustrative examples are developed to verify the parking planner. The performance of the present method indicates its competence in addressing parking multiple autonomous vehicles problem.