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Advanced diesel engines developed for the commercial market need to be adapted to the military requirements by OPERAS (Optimizing the injection pressure P, the Exhaust gas recirculation E, injection events Retard and/or Advance and the swirl ratio S). The different after treatment devices, already used or expected to be applied to diesel engines, require feed gases of appropriate properties for their efficient operation. To produce these gases some OPERAS are needed to control the diesel combustion process. Since military vehicles do not need the after treatment devices, the OPERAS of the commercial engines should be modified to meet the military requirements for high power density, better fuel economy, reduction of parasitic losses caused by the cooled EGR system, and reduction of invisible black and white smoke in the field.

The strain-life approach is now commonly used for fatigue life analysis and predictions in the ground vehicle industry. This approach requires the use of material properties obtained from strain-controlled uniaxial fatigue tests. These properties include fatigue strength coefficient (σf′), fatigue strength exponent (b), fatigue ductility coefficient (εf′), fatigue ductility exponent (c), cyclic strength coefficient (K′), and cyclic strain hardening exponent (n′). To obtain the aforementioned properties for the material, raw data from stable cyclic stress-strain loops are fitted in log-log scale. These data include total, elastic and plastic strain amplitudes, stress amplitude, and fatigue life. Values of the low cycle fatigue properties (σf′, b, εf′, c) determined from the raw data depend on the method of measurement and fitting. This paper examines the merits and influence of using different measurement and fitting methods on the obtained properties.

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.

EGR is a proven technology used to reduce NOx formation in both compression and spark ignition engines by reducing the combustion temperature. In order to further increase its efficiency the recirculated gases are subjected to cooling. However, this leads to a higher load on the cooling system of the engine, thus requiring a larger radiator. In the case of turbocharged engines the large variations of the pressures, especially in the exhaust manifold, produce a highly pulsating EGR flow leading to non-steady-state heat transfer in the cooler. The current research presents a method of determining the pulsating flow field and the instantaneous heat transfer in the EGR heat exchanger. The processes are simulated using the CFD code FIRE (AVL) and the results are subjected to validation by comparison with the experimental data obtained on a 2.5 liter, four cylinder, common rail and turbocharged diesel engine.

Cavitating flows inside a two-dimensional valve covered orifice (VCO) nozzle were simulated by using the Space-Time Conservation Element and Solution Element (CE/SE) method in conjunction with a homogeneous equilibrium cavitation model. As a validation for present model, cavitation over a NACA0015 hydrofoil was predicted and compared with previous simulation results as well as experimental observations. The model was then used to investigate the effects on internal cavitating flows of different nozzle design parameters, such as the hole size, hole aspect-ratio, hydro-erosion radius, and orifice inclination. Under different conditions, cavitating flows through fuel injectors generated hydraulic flip, supercavitation, full cavitation, and cyclical cavitation phenomena, which are commonly observed in experiments.

Many metrics have been used in an attempt to predict the effects of secondary tasks on driving behavior. Such metrics often give rise to seemingly paradoxical results, with one metric suggesting increased demand and another metric suggesting decreased demand for the same task. For example, for some tasks, drivers maintain their lane well yet detect events relatively poorly. For other tasks, drivers maintain their lane relatively poorly yet detect events relatively well. These seeming paradoxes are not time-accuracy trade-offs or experimental artifacts, because for other tasks, drivers do both well. The paradoxes are resolved if driver demand is modeled in two orthogonal dimensions rather than a single “driver workload” dimension. Principal components analysis (PCA) was applied to the published data from four simulator, track, and open road studies of visual-manual secondary task effects on driving.

An equation has been derived to calculate the burning velocity in a CFR engine from the measured flame speed under different turbulent flow fields. The turbulence is generated during the intake stroke as the fresh charge flows through different perforated 360° shrouded intake valves. The shrouds have holes of different sizes, but of the same total flow area. Results show that these valves decrease the cycle-to-cycle variation and produce higher burning velocities than conventional valves, particularly at higher engine speeds. The burning velocity depends on the Reynolds number as well as the turbulence scale.

Gasoline Direct Injection (GDI) engine has a significant fuel economy improvement over the traditional port fuel injection engine. The tradeoff for this benefit is excessive exhaust emissions, especially NOx. Three-way-catalyst (TWC) is inefficient to treat NOx emission during lean operation. So Lean NOx Trap (LNT) is invented for NOx aftertreatment and it has both storage mode and purge mode. Research on modeling and control of LNT has been conducted, but it is still lack of the essential information on the temperature effect. This research focuses on the impact of trap temperature on LNT storage time, purge time and fuel economy. The mechanism of temperature effect on LNT is investigated at first. Then the temperature control strategy based on fuel economy improvement is proposed.

At the collision moment, a driver’s lower extremity will be in different foot position, which leads to the different posture of the lower extremity with various muscle activations. These will affect the driver’s injury during collision, so it is necessary to investigate further. A simulated collision scene was constructed, and 20 participants (10 male and 10 female) were recruited for the test in a driving simulator. The braking posture and muscle activation of eight major muscles of driver’s lower extremity (both legs) were measured. The muscle activations in different postures were then analyzed. At the collision moment, the right leg was possible to be on the brake (male, 40%; female, 45%), in the air (male, 27.5%; female, 37.5%) or even on the accelerator (male, 25%; female, 12.5%). The left leg was on the floor all along.

With the mass movement toward electrification and renewable technologies, the scope of innovation of electrification has gone beyond the automotive industry into areas such as electric motorcycle applications. This paper provides a discussion of the methodology and complexities of converting an internal combustion motorcycle to an electric motorcycle. In developing this methodology, performance goals including, speed limits, range, weight, charge times, as well as riding styles will be examined and discussed. Based on the goals of this paper, parts capable of reaching the performance targets are selected accordingly. Documentation of the build process will be presented along with the constraints, pitfalls, and difficulties associated with the process of the project. The step-by-step process that is developed can be used as a guideline for future build and should be used as necessary.

Inflatable space structures can have lower launching cost and larger habitat volume than their conventional rigid counterparts. These structures are made of composite laminates, and they are flexible when folded and partially inflated. They contain light-activated resins, and can be cured with the sun light after being inflated in space. A spacecraft can burst due to cracks caused by meteor showers or debris. Therefore, it is critical to identify the important fracture failure modes, and assess their probability. This information will help a designer minimize the risk of failure and keep the mass and cost low. This paper presents a probabilistic approach for finding the required thickness of an inflatable habitat shell for a prescribed reliability level, and demonstrates the superiority of probabilistic design to its deterministic counterpart.

The central performance requirement for electrochemical energy storage systems for the full power-assist hybrid electric vehicle (HEV) is pulse power capability, typically 25-40 kW pulse power capability for 10 seconds duration. Standard test procedures utilize constant current pulses. However, in the HEV application, the power transient for acceleration is a ramped power transient and the power transient for regenerative braking power is a descending power ramp. This paper compares the usable power capability of batteries and supercapacitors under constant current, constant power, and ramped power transients. Although the usable battery discharge power is relatively insensitive to the transient type applied, 10-40% higher regenerative braking charge capability is observed with ramped power transients. With supercapacitors, the discharge and charge capability is much more strongly dependent on the type of power transient.

With the rapid development of artificial intelligence, the autonomous vehicles (AV) have attracted considerable attention in the automotive industry. However, different factors negatively impact the adoption of the AVs, delaying their successful commercialization. Accretion of atmospheric icing, especially wet snow, on AV sensors causes blockage on their lenses, making them prone to lose their sight, in turn, increasing potential chances of accidents. In this study, two different designs are proposed in order to prevent snow accretion on the lenses of AVs via air flow across the lens surface. In both designs, lenses made of plain glass and superhydrophobic coated glass surfaces are tested. While some researchers have shown promise of water repellency on superhydrophobic surfaces, more snow accretion is observed on the superhydrophobic surfaces, when compared to the plain glass lenses.

A series of rear impact tests of varying severity was performed using a mini pick-up truck with an instrumented Hybrid III dummy at the driver position. Head, neck and chest loads were monitored. The severities of these loads from an injury standpoint were assessed using biomechanically based reference criteria that are particularly suitable for the Hybrid III. The glass Installation performed well as a head restraint. Glass fracture from head impact was achieved only when the glass was predamaged, with surface scratches on the outer (tensile) side. The amazing strength and flexibility of tempered glass and the dramatic reduction in strength caused by small surface scratches are demonstrated.

It is recognized that the heavier vehicles, the more emissions, thus the more imperative to electrify. In this study, long haul heavy-duty trucks are referred as HDTs, which are recognized as one of the hard-to-electrify vehicle segments, though the automotive industry has gained trending advantages of electrifying both light-duty cars and SUVs. Since big rigs such as Class 8 HDTs have significant road-block challenges for electrification due to the demanding long-hour work cycles in all weathers, this study focuses on quantifying those electrification challenges by taking advantage of the public data of Class 8 tractors & trailers. Tesla Semi is the research target though its vehicle spec data is sorted out with fragmentary information in the public domain. The key task is to analyze the battery capacity requirements due to environmental temperature and inherent aging over the lifespan.

The Wayne State University (WSU) EcoCAR2 student team designed, modeled, Model-In-the-Loop (MIL) tested, Software-In-the-Loop (SIL) simulation tested, and Hardware-In-the-Loop (HIL) simulation tested the team's conversion design for taking a 2013 Chevrolet Malibu and converting it into a Parallel-Through-The-Road (PTTR) plug-in hybrid. The 2013 Malibu is a conventional Front Wheel Drive (FWD) vehicle and the team's conversion design keeps the conventional FWD and adds a Rear Wheel Drive (RWD) powertrain consisting of an electric motor, a single speed reduction gearbox and a differential to drive the rear wheels -where none of these previously existed on the rear wheels. The RWD addition creates the PTTR hybrid powertrain architecture of two driven axles where the mechanical torque path connection between the two powertrains is through the road, rather than a mechanical torque path through gears, chains, or shafts.

The Wayne State University (WSU) EcoCAR 2 Team designed the conversion of a GM donated 2013 Chevrolet Malibu to a Parallel-Through-The-Road (PTTR) Plug-In Hybrid vehicle within a 9 month timeframe. This fast prototyping project used the EcoCAR 2 Vehicle Development Process (EVDP). Various tradeoffs were made to meet all competition requirements and to make the vehicle as competitive as possible within budget, time and experience limitations. The chosen PTTR architecture, nicknamed by the team as “E2D2” (Ethanol-Electric Dual-Drivetrain), provides up to 35.7 electric only miles and a fuel economy of 60 miles per gallons gasoline equivalent (mpgge) or 3.96 liters gasoline equivalent (lge) per one hundred km. This is accomplished using an E85 engine-driven front traction system and a battery-electric-motors-driven rear traction system. The team developed the control system and designed the packaging and integration of all required components including the Energy Storage System (ESS).

There is a general interest in the reduction of cooling loads in military vehicles. To that end thermal barrier coatings (TBCs) are being studied for their potential as insulators, particularly for military engines. The effectiveness of TBCs is largely dependent on their thermal properties, however insulating effects can also be modified by applying different coating thickness. Convection from in-cylinder surfaces can also be affected by manipulation of surface structure. Although most prior studies have examined TBCs as a means of increasing efficiency, military vehicle design is primarily concerned with the reduction of cylinder heat transfer to allow downsizing of cooling systems. A 1-D transient conjugate heat transfer model was developed to provide insight into the effects of different TBC designs and material selection on cooling loads. Results identify low thermal conductivity and low thermal capacitance as key parameters in achieving optimal heat loss reduction.

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.

This paper details the vehicle testing activities performed during the Year 4 of the EcoCAR 3 competition by the Wayne State University team on a Pre-Transmission Parallel PHEV. The paper focuses on two main testing platforms: the chassis dynamometer and the closed-course track (on-road). The focus of the former is to evaluate the emissions and energy consumption associated with different driving scenarios, while the latter has been used to assess the vehicle performance and their impact on the consumer appeal. The paper presents the objectives of each test, the setup accomplished for the different vehicle testing platforms, the results obtained and the comparison with the values expected from simulations. In addition, the impact of the results on the refinement of the control strategies and on the validation of the simulation models are discussed.