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Liquid ammonia is an ideal zero carbon fuel to reduce carbon emission of internal combustion engines. The high-pressure injection of liquid ammonia is a key technology to fast distribute fuels and prepare better combustion performances. The physical properties of liquid ammonia are different to traditional fossil fuels including diesel and gasoline, which can change the spray and droplet characteristics significantly. However, the spray droplet characteristics of liquid ammonia injection is lack of investigations. In this paper, Phase Doppler Particle Analyzer (PDPA) are used to measure the droplet diameter and velocity of high-pressure liquid ammonia sprays up to 75 MPa and compare to diesel sprays. Effects of flash boiling of liquid ammonia droplet characteristics are also analyzed.

Enhanced protection against high speed crashes requires more aggressive passive safety countermeasures as compared to what are provided in vehicle structures today. Apart from such collision-related scenarios, high energy explosions, accidentally caused or otherwise, require superior energy-absorbing capability of vehicle body subsystems. A case in point is a passenger vehicle subjected to an underbody blast emanating shock wave energy of military standards. In the current study, assessment of the behavior of a “hollow” countermeasure in the form of a depressed steel false floor panel attached with spot-welds along flanges to a typical predominantly flat floor panel of a car is initially carried out with an explicit LS-DYNA solver. This is followed up with the evaluation of PU (polyurethane) foam-filled and liquid-filled false floor countermeasures. In all cases, a charge is detonated under the false floor subjecting it to a high-energy shock pressure loading.

In this decade, the detailed multi-layer FE model is always applied for investigating the mechanical behavior of Li-ion batteries under mechanical abuse. However, establishing a detailed model of different types of batteries requires a series of material characterization of components. To improve the efficiency of the procedure of component calibration, we introduce a procedure of automatic coating material characterization as an example to represent the strategy. The proposed method is constructing a response solver through MATLAB to predict the mechanical behavior of the coating specimen's representative volume element (RVE) under designated test conditions. The coating material is represented through Drucker-Prager-Cap (DPC) model. All parameters, including boundary conditions and material parameters, are included in this solver.

In automotive body manufacturing the dies for blanking/trimming/piercing are under most severe loading condition involving high contact stress at high impact loading and large number of cycles. With continuous increase in sheet metal strength, the trim die service life becomes a great concern for industries. In this study, competing trim die manufacturing routes were compared, including die raw materials produced by hot-working (wrought) vs. casting, edge-welding (as repaired condition) vs. bulk base metals (representing new tools), and the heat treatment method by induction hardening vs. furnace through-heating. CaldieTM, a Uddeholm trademarked grade was used as trim die material. The mechanical tests are performed using a WSU developed trimming simulator, with fatigue loading applied at cubic die specimen’s cutting edges through a tungsten carbide rod to accelerate the trim edge damage. The tests are periodically interrupted at specified cycles for measurement of die edge damage.

According to the statistics of National Highway Traffic Safety Administration, driver’s cognitive distraction, which is usually caused by drivers using mobile phones, has become one of the main causes of traffic accidents. To solve this problem and guarantee the safety of man-vehicle-road system, the most critical work is to improve the accuracy of driver’s cognitive state detection. In this paper, a novel driver’s cognitive state detecting method based on LightGBM (Light Gradient Boosting Machine) is proposed. Firstly, cognitive distraction experiments of making calls are carried out on a driving simulator to collect vehicle states, eye tracking and EEG (electron encephalogram) data simultaneously and feature extraction is conducted. Then a classifier considering road and individual characteristics used for detecting cognitive states is trained based on LightGBM algorithm, with 3 predefined cognitive states including concentration, ordinary distraction and extreme distraction.

Adhesive bonding provides a versatile strategy for joining metallic as well as non-metallic substrates, and also offers the functionality for joining dissimilar materials. In the design of unibody vehicles for NVH (Noise, Vibration and Harshness) performance, adhesive bonding of sheet metal parts along flanges can provide enhanced stiffening of body-in-white (BIW) leading to superior vibration resistance at low frequencies and improved acoustics due to sealing of openings between flanges. However, due to the brittle nature of adhesives, they remain susceptible to failure under impact loading conditions. The viability of structural adhesives as a sole or predominant mode of joining stamped sheet metal panels into closed hollow sections such as hat-sections thus remains suspect and requires further investigation.

Vehicle weight-driven design comes amid rising higher fuel efficiency standards and must meet the criteria—pass proving ground (PG) test events that are equivalent to customer usage. Computer-aided engineering (CAE) fatigue analysis for PG is a successful push behind to digitally simulate vehicle durability performance with high fidelity. The need for vehicle weight reduction often arises in the vehicle development final phases when CAE methods, time, and tangible cost-effective opportunities are limited or nonexistent. In this research, a new CAE methodology is developed to identify opportunities for lightweight hole placement in the chassis structure and deliver a cost-effective lightweight solution with no additional impact on fatigue life. The successful application of this new methodology exhibits the effectiveness of the truck frame, which is the key chassis structure to support the body, suspension, and powertrain.

The Hotelling multivariate control chart and the sample generalized variance |S| are used to monitor the mean and dispersion of vehicle build vision data including the pallet information to identify the non-conforming pallets that are used in body shops of FCA US LLC assembly plants. An iterative procedure and the Gaussian mixture model (GMM) are used to rank the non-conforming or bad pallets in the order of severity. The Hotelling multivariate T2 test statistic along with Mason-Tracy-Young (MYT) signal decomposition method is used to identify the features that are affected by the bad pallets. These algorithms were implemented in the Advanced Pallet Analysis module of the FCA US software Body Shop Analysis Toolbox (BSAT). The identified bad pallets are visualized in a scatter plot with a different color for each of the top bad pallets. The run chart of an affected feature confirms the bad pallet by highlighting data points from the bad pallet.

A novel fault tolerant brake strategy for In-wheel motor driven electric vehicles based on integral sliding mode control and optimal online allocation is proposed in this paper. The braking force distribution and redistribution, which is achieved in online control allocation segment, aim at maximizing energy efficiency of the vehicle and isolating faulty actuators simultaneously. The In-wheel motor can generate both driving torque and braking torque according to different vehicle dynamic demands. In braking procedure, In-wheel motors generate electric braking torque to achieve energy regeneration. The strategy is designed to make sure that the stability of vehicle can be guaranteed which means vehicle can follow desired trajectory even if one of the driven motor has functional failure.

Accident statistics have shown that older and obese occupants are less adaptable to existing vehicle occupant restraint systems than ordinary middle-aged male occupants, and tend to have higher injury risk in vehicle crashes. However, the current research on injury mechanism of aging and obese occupants in vehicle frontal impacts is scarce. This paper focuses on the optimization design method of occupant restraint system parameters for specific body type characteristics. Three parameters, namely the force limit value of the force limiter in the seat belt, pretensioner preload of the seat belt and the proportionality coefficient of mass flow rate of the inflator were used for optimization. The objective was to minimize the injury risk probability subjected to constraints of occupant injury indicator values for various body regions as specified in US-NCAP frontal impact tests requirements.

The explosion of big data has created challenges for both cloud-based systems and Autonomous Vehicles (AVs) in data collection and management. The same challenges are now being realized in developing databases for integrated sensors, streaming, real-time and on-demand services in AVs. With just one AV expecting to generate over 30 Terabytes of data a day, modern NoSQL databases provide opportunities to horizontally scale AV data seamlessly. NoSQL provides solutions designed to accommodate a wide variety of data models such as, key-value, document, column and graph databases. Key-value stores are by nature scalable, fast processing, and distribute horizontally. These databases are tasked with handling several data types including IoT, radar, lidar, ultra-sonic sensors, GPS, odometry, and sensor data while providing streaming and real-time services. NoSQL can store and utilize structured, semi-structured, and unstructured data necessary for multimedia storage needs.

A hydraulic chamber is embedded in serial with the accumulator of a normal mono-tube magnetorheological fluid damper (MRFD). The damper stiffness can be adjusted by changing the accumulator volume with the hydraulic chamber. The hydraulic chamber is connected to an electric pump and controlled by the braking-by-wire (BBW) system. A modified bi-viscosity magnetorheological fluid (MRF) model that explicitly includes the parameter of control current is proposed. A dynamic model of this hydraulic MRFD is subsequently set up based on the MRF model. Experiments are conducted to validate the model and simulations are carried out to study the influences of accumulator volume on the external performances. Results show that the hydraulic chamber is able to provide rapid variations of the external force through accumulator volume changes.

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.

Due to the variation of compartment design and occupant’s posture in self-driving cars, there is a new and major challenge for occupant protection. In particular, the studies on occupant restraint systems used in the self-driving car have been significantly delayed compared to the development of the autonomous technologies. In this paper, a numerical study was conducted to investigate the effectiveness of three typical restraint systems on the driver protection in three different scenarios.

There has been recent progress over the past 10 years in research comparing 6-year-old thoracic and abdominal response of pediatric volunteers, pediatric post mortem human subjects (PMHS), animal surrogates, and 6-year-old ATDs. Although progress has been made to guide scaling laws of adult to pediatric thorax and abdomen data for use in ATD design and development of finite element models, further effort is needed, particularly with respect to lateral impacts. The objective of the current study was to use the impact response data of age equivalent swine from Yaek et al. (2018) to assess the validity of scaling laws used to develop lateral impact response corridors from adult porcine surrogate equivalents (PSE) to the 3-year-old, 6-year-old, and 10-year-old for the thorax and abdominal body regions.

The use of deposit control additives in European market gasoline is well documented for maintaining high levels of engine cleanliness and subsequent sustained fuel and emissions performance. Co-ordinating European Council (CEC) industry fuels tests have played a crucial role in helping to drive market relevant, effective and low-cost deposit control additives into European market fuels. Until now, there hasn’t been a Gasoline Direct Injection engine test available to fuel marketers in any market globally. However, a new CEC engine test is currently being developed to address that gap. Based on an in-house VW injector coking test, it shows promise for becoming a useful tool with which to develop and measure the performance of deposit control additives. A key requirement of industry tests should be to replicate issues seen in consumer vehicles, thereby providing a platform for relevant solutions.

Active collision avoidance can assist drivers to avoid longitudinal collision through active brake. Regenerative braking can improve the driving range and braking response speed. At this stage, conventional hydraulic braking system limits the implements of above technologies because of its poor performance of response speed and coordinated control. While the brake-by-wire system is a better actuator that can fulfill requirements of automotive electric and intelligent development due to its rapid response and flexible adjustment. However, the system control algorithm becomes more complicated with introduction of regenerative braking and active collision avoidance function, which is also the main problem solved in this paper.

Previous study suggested that female, thin, obese, and older occupants had a higher risk of death and serious injury in motor vehicle crashes. Human body finite element models were a valuable tool in the study of injury biomechanics. The mesh deformation method based on radial basis function(RBF) was an attractive alternative for morphing baseline model to target models. Generally, when a complex model contained many elements and nodes, it was impossible to use all surface nodes as landmarks in RBF interpolation process, due to its prohibitive computational cost. To improve the efficiency, the current technique was to averagely select a set of nodes as landmarks from all surface nodes. In fact, the location and the number of selected landmarks had an important effect on the accuracy of mesh deformation. Hence, how to select important nodes as landmarks was a significant issue. In the paper, an efficient peak point-selection RBF mesh deformation method was used to select landmarks.

Fiber composite materials are widely used in many industrial applications - specially in automotive, aviation and consumer goods. Introducing light-weighting material solutions to reduce vehicle mass is driving innovative materials research activities as polymer composites offer high specific stiffness and strength compared to contemporary engineering materials. However, there are issues related to high production volume, automation strategies and handling methods. The state of the art for the production of these light-weight flexible textile or composite fiber products is setting up multi-stage manual operations for hand layups. Material handling of flexible textile/fiber components is a process bottleneck. Consequently, the long term research goal is to develop semi-automated pick and place processes for flexible materials utilizing collaborative robots within the process. Collaborative robots allow for interactive human-machine tasks to be conducted.

Analysis and validation of current scaling relationships and existing response corridors using animal surrogate test data is valuable, and may lead to the development of new or improved scaling relationships. For this reason, lateral pendulum impact testing of appropriate size cadaveric porcine surrogates of human 3-year-old, 6-year-old, 10-year-old, and 50th percentile male age equivalence, were performed at the thorax and abdomen body regions to compare swine test data to already established human lateral impact response corridors scaled from the 50th percentile human adult male to the pediatric level to establish viability of current scaling laws. Appropriate Porcine Surrogate Equivalents PSE for the human 3-year-old, 6-year-old, 10-year-old, and 50th percentile male, based on whole body mass, were established. A series of lateral impact thorax and abdomen pendulum testing was performed based on previously established scaled lateral impact assessment test protocols.