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Inspired by the cross-section of a beetle’s elytron, hyperbolic lattice with double-layered feature has received increasing attention in recent years. This paper aims to investigate the compression behavior and energy absorption performance of a truss-based hyperbolic structure. The quasi-static compression simulation for the hyperbolic structure has been performed and validated with a compression test. Through compression simulation and test, the hyperbolic structure proved to show obvious twisting effect. To explore the influences of the geometric parameters in the mechanical properties of hyperbolic structure, this paper has designed 13 cells with varied rotation angle, height, and rod diameter, and investigated the mechanical properties of these configurations.

The origami structures have received increasing attention in recent years due to the high stiffness ratio and lightweight feature. This paper has proposed an origami-based honeycomb structure and investigated the mechanical properties of the structure. The compression response and energy absorption of the structure under quasi-static loading have been investigated experimentally and numerically. The numerical results closely matched the experimental results in terms of the compression force curve and deformation patterns. The effects of different structural parameters on the mechanical response and energy absorption characteristics were analyzed with the validated model. Finally, the comparative results show that the origami-inspired honeycomb structure, which is characterized by rotational folding mode under axial compression, has better performance in terms of mechanical response and energy absorption.

A multiple-injection combustion strategy has been developed for heated gasoline direct injection compression ignition (HGCI). Gasoline was injected into a 0.4L single cylinder engine at a fuel pressure of 300bar. Fuel temperature was increased from 25degC to a temperature of 280degC by means of electric injector heater. This approach has the potential of improving fuel efficiency, reducing harmful CO and UHC as well as particulate emissions, and reducing pressure rise rates. Moreover, the approach has the potential of reducing fuel system cost compared to high pressure (>500bar) gasoline direct injection fuel systems available in the market for GDI SI engines that are used to reduce particulate matter. In this study, a multiple injection strategy was developed using electric heating of the fuel prior to direct fuel injection at engine speed of 1500rpm and load of 12.3bar IMEP.

The aim of this study is to develop a pathway towards Hydrogen combustoin on an opposed-piston four stroke engine (OP4S) by using 1D simulation code from Gamma Technologies. By its configuration, the OP4S engine has significant thermal efficiency benefits versus conventional ICE. The benefit of the OP4S is reduced heat losses due to elimination of the cylinder head, which increase the brake thermal efficiency. A hydrogen-fueled (H2) opposed-piston four stroke (OP4S) engine was modeled using GTPower to determine the potential on performance, thermal efficiency and emissions targets. The 1D model was first validated on E10 gasoline using experimental data and was used to explore changes to fuel type in NG and H2, fueling location (TPI and DI), fuel mixture strength (stoichiometric and lean), for an optimized plenum volume and turbocharger selection.

The increase in regulatory demand to reduce CO2 emissions resulted in a focus on the development of novel combustion modes such as gasoline compression ignition (GCI). It has been shown by others that GCI can improve the overall engine efficiency while achieving soot and NOx emissions targets. In comparison with diesel fuel, gasoline has a higher volatility and has more resistance to autoignition, therefore, it has a longer ignition delay time which facilitates better mixing of the air-fuel charge before ignition. In this study, a GCI combustion system has been tested using a 2.2L compression ignition engine as part of a US Department of Energy funded project. For this purpose, a multiple injection strategy was developed to improve the pressure rise rates and soot emission levels for the same engine out NOx emissions.

Over the past decade there has been significant development in Automated Driving (AD) with continuous evolution towards higher levels of automation. Higher levels of autonomy increase the vehicle Dynamic Driving Task (DDT) responsibility under certain predefined Operational Design Domains (in SAE level 3, 4) to unlimited ODD (in SAE level 5). The AD system should not only be sophisticated enough to be operable at any given condition but also be reliable and safe. Hence, there is a need for Automated Vehicles (AV) to undergo extensive open road testing to traverse a wide variety of roadway features and challenging real-world scenarios. There is a serious need for accurate Ground Truth (GT) to locate the various roadway features which helps in evaluating the perception performance of the AV at any given condition. The results from open road testing provide a feedback loop to achieve a mature AD system.

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.

As the number of electric vehicles (EVs) within society rapidly increase, the concept of maximizing its efficiency within the electric smart grid becomes crucial. This research presents the impacts of integrating EV charging infrastructures within a smart grid through a vehicle to grid (V2G) program. It also observes the circulation of electric charge within the system so that the electric grid does not become exhausted during peak hours. This paper will cover several different case studies and will analyze the best and worst scenarios for the power losses and voltage profiles in the power distribution system. Specifically, we seek to find the optimal location as well as the ideal number of EVs in the distribution system while minimizing its power losses and optimizing its voltage profile. Verification of the results are primarily conducted using GUIs created on MATLAB.

As vehicles are getting electrified and more intelligent, the energy consumption of the auxiliary system increases rapidly. The auxiliary battery acts as the backbone of the system to support the proper operation of the vehicle. It is important to ensure the auxiliary battery has enough energy to meet the basic loads regardless the vehicle is in park or running. However, the existing methods only focus on auxiliary energy management when the vehicle is in a dynamic event. To fulfill the gap, we propose an intelligent strategy that detects the low state of charge (SOC) condition, temporarily turns down the auxiliary loads based on their priorities and charges the auxiliary battery at the maximum efficiency of the auxiliary power unit. In addition, the proposed strategy allows the vehicle to get the park duration update and make intelligent decisions on charging the auxiliary battery.

Today’s advanced vehicles have high degree of interaction due to numerous sensors, actuators and also with complex communication within the control units. In order to hack a vehicle, it has to be within a certain range of communication. Here, we discuss the On-Board Diagnostic (OBD) regulations for next generation BEV/HEV, its vulnerabilities and cybersecurity threats that come with hacking. We propose three cybersecurity attack detection and defense methods: Cyber-Attack detection algorithm, Time-Based CAN Intrusion Detection Method and, Feistel Cipher Block Method. These control methods autonomously diagnose a cybersecurity problem in a vehicle’s onboard system using an OBD interface, such as OBD-II when a fault caused by a cyberattack is detected, All of this is achieved in an internal communication network structure. The results discussed here focus on the first detection method that is Cyber-Attack detection algorithm.

Regenerative braking is identified as an essential step toward extending cruising mileage for electric vehicle (EV). Braking energy recovery strategies usually focus on passenger EV and commercial EV is ignored. In this paper, an energy-efficient braking torque distribution strategy is proposed for a rear-axle drive commercial EV to improve braking energy recovery and safety. Firstly, the braking force distribution curve is determined referring to the EU braking law for commercial vehicle and the ideal braking distribution curve. Secondly, a novel braking torque distribution strategy is established adopting fuzzy control algorithm, where the ratio between hydraulic braking torque and regenerative braking torque is updated instantaneously according to vehicle velocity, braking strength and state of charge of battery. Then, the corresponding controller is synthesized on ideal braking condition and several classic cycles.

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.

Use of ethanol as gasoline replacement can contribute to the reduction of nitrogen oxide (NOx) and carbon oxide (CO) emissions. Depending on ethanol production, significant reduction of greenhouse-gas emissions is possible. Concentration of certain species, such as unburned ethanol and acetaldehyde in the engine-out emissions are known to rise when ratio of ethanol to gasoline increases in the fuel. This research explores on hydrous ethanol fueled port-fuel injection (PFI) spark ignition (SI) engine emissions that contribute to photochemical formation of ozone, or so-called ozone precursors and the precursor of peroxyacetyl nitrates (PANs). The results are compared to engine operation on gasoline. Concentration obtained by FTIR gas analyzer, and mass-specific emissions of formaldehyde (HCHO), acetaldehyde (MeCHO) and methane (CH4) under two engine speed, four load and two spark advance settings are analyzed and presented.

Lithium-ion polymer battery has been widely used for vehicle onboard electric energy storage ranging from 12V SLI (Starting, Lighting, and Ignition), 48V mild hybrid electric, to 300V battery electric vehicle. Formulation on cell parameters acquired from minimum numbers of experiments, the modeling and simulation could be an effective approach in predicting battery performance, thermal effectiveness, and degradation. This paper describes the modeling, simulation, and validation of Lithium-Nickel-Manganese-Cobalt-Oxide (LiNiMnCoO2) based cell with 3.6V nominal voltage and 20Ah capacity. Constant current 20A, 40A, 60A, and 80A discharge tests are conducted in the computer-controlled cycler and temperature chamber. Discharging voltage curves and cell surface temperature distributions are recorded in each discharging test. A three-dimensional cell model is constructed in the COMSOL multi-physics platform based on the cell parameters.

Automated driving functionalities delivered through Advanced Driver Assistance System (ADAS) have been adopted more and more frequently in consumer vehicles. The development and implementation of such functionalities pose new challenges in safety and functional testing and the associated validations, due primarily to their high demands on facility and infrastructure. This paper presents a rather unique Vehicle-in-the-Loop (VIL) test setup and methodology compared those previously reported, by combining the advantages of the hardware-in-the-loop (HIL) and traditional chassis dynamometer test cell in place of on-road testing, with a multi-agent real-time simulator for the rest of test environment.

Internal combustion engines are required to achieve production goals of better fuel economy, improved fuel economy and reduced emissions in order to meet the current and future stringent standards. To achieve these goals, it is essential to control the combustion process using an in-cylinder combustion sensor and a system that produces a feedback signal to the ECU. This paper presents a system based on combustion ionization that includes a newly developed smart spark plug capable of sensing the whole combustion process. A unique feature of the smart spark plug system is its ability to sense the early stages of combustion and produce a complete ion current signal that accurately identifies and can be used for the control of the start of combustion.

The Department of Defense (DOD) has adopted the use of JP-8 under the “single battlefield fuel” policy. Fuel properties of JP-8 which are different from ULSD include cetane number, density, heating value and compressibility (Bulk modulus). While JP8 has advantages compared to ULSD, related to storage, combustion and lower soot emissions, its use cause a drop in the peak power in some military diesel engines. The engines that has loss in power use the Hydraulically actuated Electronic Unit Injection (HEUI) fuel system. The paper explains in details the operation of HEUI including fuel delivery into the injector and its compression to the high injection pressure before its delivery in the combustion chamber. The effect of fuel compressibility on the volume of the fuel that is injected into the combustion chamber is explained in details.

In order to reflect the actual power consumption of logistics electric vehicles in a city, sample real vehicle road data. After preprocessing, the short-stroke analysis method is used to divide it into working blocks of no less than 20 seconds. Based on principal component analysis, three of the 12 characteristic parameters were selected as the most expressive. K-means clustering algorithm is adopted to obtain the proportions of various short strokes, according to the proportion, select the short stroke with small deviation degree to combine, and construct the driving cycle, it has the characteristics of low average speed, high idle speed ratio and short driving distance. AVL-cruise software builds the vehicle model and runs the driving cycle of urban logistic EV. Compared with WLTC, the difference in power consumption is 34.3%, which is closer to the actual power consumption, the areas with the highest motor speed utilization are concentrated only in the idle area.

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.

Gearbox fault diagnosis is one of the core research areas in the field of rotating machinery condition monitoring. The signal processing-based bearing fault diagnosis in the gearbox is considered as challenging as the vibration signals collected from acceleration transducers are, in general, a mixture of signals originating from an unknown number of sources, i.e. an underdetermined blind source separation (UBSS) problem. In this study, an effective UBSS-based algorithm solution, that combines empirical mode decomposition (EMD) and kernel independent component analysis (KICA) method, is proposed to address the technical challenge. Firstly, the nonlinear mixture signals are decomposed into a set of intrinsic mode function components (IMFs) by the EMD method, which can be combined with the original observed signals to reconstruct new observed signals. Thus, the original problem can be effectively transformed into over-determined BSS problem.