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Universal Connectivity in the vehicle is no longer a nice-to-have function, but a critical tool to support every other function of the car - infotainment, active safety, autonomous driving, diagnostics, driving comfort etc. Although CASE (Connectivity, Autonomous, Services, Electrification) is now a commonly accepted foundation of new technology, it should perhaps be more accurately described as “C + ASE”, since Connectivity is an important enabler for the other three. Typically, connectivity in a vehicle implies primarily cellular (terrestrial) communication along with several other wireless protocols such as WiFi, Bluetooth, NFC etc. In addition, emerging vehicular technologies such as autonomous driving would potentially require ubiquitous and highly reliable connectivity.

Due to the limitations on resistance spot welding of ultra-thin steel sheet (thicknesses below 0.5 mm) in high-volume automotive manufacturing, a comparison of friction stir spot welding and self-piercing riveting was performed to determine which process may be more amenable to enabling assembly of ultra-thin steel sheet. Statistical comparisons between mechanical properties of lap-shear tensile and T-peel were made in sheet thickness below 0.5 mm and for dissimilar thickness combinations. An evaluation of energy to fracture, fracture mechanisms, and joint consistency is presented.

As the automotive industry prepares to roll out an unprecedented range of fully electric propulsion vehicle models over the next few years - it really brings to a head for folks responsible for brakes what used to be the subject of hypothetical musings and are now pivotal questions for system design. How do we really go about designing brakes for electric vehicles, in particular, for the well-known limit condition of descending a steep grade? What is really an “optimal’ design for brakes considering the imperatives for the entire vehicle? What are the real “limit conditions” for usage that drive the fundamental design? Are there really electric charging stations planned for or even already existing in high elevations that can affect regenerative brake capacity on the way down? What should be communicated to drivers (if anything) about driving habits for electric vehicles in routes with significant elevation change?

Lagrangian approach has been widely adopted in the droplet impingement analysis for aircraft icing simulation. Some improvements were proposed, including: 1) The heat and mass transfer consideration in droplet dynamics; 2) More efficient droplet localization method, which could and facilitated to find the initial cell in Eulerian grid; 3) New computation method of impingement efficiency, which uses the cover ratio to transform the impingement efficiency of arbitrary impinged region to that of the cell element of body surface and avoids the iterative computation to find the trajectories reaching the corner of the panel or cell element. A numerical solver was built and integrated with the capabilities to deal with super-cooled large droplet (SLD) conditions by considering the splashing and bouncing of SLD. The computational results were validated with the experiment data, which shown good agreements in the impingement limitations and tendency.

Electric Vehicles are typically thought of as being quiet and refined, but they do come with some unique N&V challenges. Some of these challenges include a natural sound that can be undesirable due to its tonal nature, presence of high frequency, discontinuities in sound, and characteristics and levels that do not always naturally increase with motor torque and vehicle speed. One approach to address those challenges is Electric Vehicle Sound Enhancement (EVSE) which is a software feature embedded within the infotainment system. EVSE can be used to improve the perception of the vehicle by enhancing the preferred natural sounds of the vehicle, masking unusual and annoying components of the sound and aurally conveying information related to the vehicle performance. A jury study was conducted to better understand how EVSE can be used to accomplish this.

The amount of acidic material in used engine oil is considered an indicator of the remaining useful life of the oil. Total acid number, determined by titration, is the most widely accepted method for determining acidic content but the method is not capable of speciation of individual acids. In this work, high molecular weight residue was isolated from used engine oil by dialysis in heptane. This residue was then analyzed using pyrolysis-comprehensive two dimensional gas chromatography with time-of-flight mass spectrometry. Carboxylic acids from C2-C18 were identified in the samples with acetic acid found to be the most abundant. This identification provides new information that may be used to improve the current acid detection methodologies for used engine oils.

GM has recently developed two types of plug-in electric vehicles. First is an extended range electric vehicle such as the Volt, and the second is a battery electric vehicle such as the Bolt. An overview, of traction inverter and power module used in GM battery electric vehicles, is presented. IGBT power modules are critical components used in traction inverters for driving GM Electrified Vehicles. IGBT power modules are also described in a benchmarking study using key metrics based on horizontal die configuration, layout and vertical thermal stack. Power Module evaluation test set up, procedure and instrumentation used in GM Power Module Lab, Pontiac, Michigan are described. GM Electrification development journey depends on IGBT power module passive test benches; turn on/off energy loss tester, thermal resistance tester, and slow/fast power cycles testers (fast junction temperature change, in seconds, and slow baseplate temperature change, in minutes).

In today's competitive market, noise and vibration are among the most important parameters that impact the success of a vehicle. In body-on-frame construction vehicles, elastomeric body mounts play a major role in isolating the passenger compartment from road noise, harshness, shake, and other vibrations in the chassis as well as improving ride quality across a wide frequency range. This paper describes the work carried out to design a fluid filled mount with high lateral stiffness that can alter the perceived Noise, Vibration and Harshness (NVH) performance of current production body-on-frame trucks. It was found that the quietness and ride qualities can be significantly improved by positioning the glycol-filled mounts at the anti-node of the frame first vertical bending mode; under the C-pillar intersection with the frame. The performance of mounts in this area is known to be critical to ride quality.

Most tractor-semitrailers are fitted with multi-axle trailers which cannot be actively steered, and such vehicles with an articulated configuration are inclined to exhibit instability such as trailer swing, jack-knifing, and rollover at high speed. Proposed in this paper is an optimal control of the yaw stability of tractor-semitrailers at high speed by applying an active trailer's steering angle. An optimal control algorithm is designed by employing a 3-DOF vehicle model in the yaw plane. The optimal linear quadratic regulator (LQR) approach is used with a cost function including sideslip angles, yaw rates of both tractor and trailer, and trailer's steering angle. The yaw stability at the high speed is also quantified by the dynamic performance measurements of lateral path deviation, hitch angle and rearward amplification (RA). The algorithm is evaluated by co-simulations using TruckSim and Matlab/Simulink softwares.

Electric vehicles have a strong potential to reduce a continued dependence on fossil fuels and help the environment by reducing pollution. Despite the desirable advantage, the introduction of electrified vehicles into the market place continues to be a challenge due to cost, safety, and life of the batteries. General Motors continues to bring vehicles to market with varying level of hybrid functionality. Since the introduction of Li-ion batteries by Sony Corporation in 1991 for the consumer market, significant progress has been made over the past 25 years. Due to market pull for consumer electronic products, power and energy densities have significantly increased, while costs have dropped. As a result, Li-ion batteries have become the technology of choice for automotive applications considering space and mass is very critical for the vehicles.

As the automotive industry quickly moves towards hybridized and electrified vehicles, the optimal integration of power electronics in these vehicles will have a significant impact not only on the cost, performance, reliability, and durability; but ultimately on customer acceptance and market success of these technologies. If properly executed with the right cost, performance, reliability and durability, then both the industry and the consumer will benefit. It is because of these interdependencies that the pace and scale of success, will hinge on effective collaboration. This collaboration will be built around the convergence of automotive and industrial technology. Where real time embedded controls mixes with high power and voltage levels. The industry has already seen several successful collaborations adapting power electronics to the automotive space in target vehicles.

The General Motors Reduced Scale Wind Tunnel Facility, which came into operation in the fall of 2015, is a new state-of-the-art scale model aerodynamic test facility that expands GM’s test capabilities. The new facility also increases GM’s aerodynamic testing through-put and provides the resources needed to achieve the growing demand for higher fuel economy requirements for next generation of vehicles. The wind tunnel was designed for a nominal model scale of 40%. The nozzle and test section were sized to keep wind tunnel interference effects to a minimum. Flow quality and other wind tunnel performance parameters are on par with or better than the latest industry standards. A 5-belt system with a long center belt and boundary layer suction and blowing system are used to model underbody flow conditions. An overhead probe traverse system is installed in the test section along with a model positioning robot used to move the model in an out of the test section.

Hybridization of vehicles is considered as the most promising technology for automakers and researchers, facing the challenge of optimizing both the fuel economy and emission of the road transport. Extensive studies have been performed on power-split hybrid electric vehicles (PS-HEVs). Despite of the fact that their excellent fuel economy performance in city driving conditions has been witnessed, a bottle neck for further improving the fuel economy of PS-HEVs has been encountered due to the inherent engine-generator-motor power circulation of the power-split system under medium-low speed cruising scenarios. Due to the special mechanical constraints of the power-split device (PSD), the conventional periodic cruising strategy like Pulse and Glide cannot be applied to PS-HEVs directly.

For virtual simulation of the vehicle attributes such as handling, durability, and ride, an accurate representation of pneumatic tire behavior is very crucial. With the advancement in autonomous vehicles as well as the development of Driver Assisted Systems (DAS), the need for an Intelligent Tire Model is even more on the increase. Integrating sensors into the inner liner of a tire has proved to be the most promising way in extracting the real-time tire patch-road interface data which serves as a crucial zone in developing control algorithms for an automobile. The model under development in Kettering University (KU-iTire), can predict the subsequent braking-traction requirement to avoid slip condition at the interface by implementing new algorithms to process the acceleration signals perceived from an accelerometer installed in the inner liner on the tire.

De-fossilization is an increasingly important trend in the energy sector. In the transport sector the de-fossilization efforts have been centered in promoting the electrification of vehicles, nonetheless other pathways, like the use of carbon neutral or carbon-offsetting fuels under current vehicle fleets, are also worth considering. Low-carbon fuels (LCF) can be synthetized from sources that can take advantage of the carbon already present in the atmosphere (either by technologies like direct carbon capture or biological processes like photosynthesis in biofuels) and use energy from renewable sources for the necessary industrial processes. Although, LCFs can be compared to fossil fuels as energy sources for internal combustion engines, their composition is not the same and their properties can modify the engine combustion and emissions.

Vehicle to Everything (V2X) communication is a prominent solution for active safety collision avoidance and for providing autonomous vehicles Non-Line of Sight (NLOS) capabilities. For safety purposes, it is essential the V2X technology would support communication between all road users, e.g., Vehicles (V2V), pedestrians (V2P) and road infrastructure (V2I). Hence, the efficiency of a V2V communication solution should be evaluated through system level performance. In addition, the examined performance metrics need to reflect safety related properties. Metrics as Packet Reception Ratio (PRR) and transmission latencies, which are commonly used to assess V2X system’s functionality, aren’t enough since reception latencies are overlooked. The latter is crucial in ensuring messages would reach their destination on time to avoid hazardous incidents. The reception cadence may be much lower than this of the transmission due to various phenomenon (e.g. channel congestion).

Regenerative braking without question greatly impacts brake pad service life in the field, in most cases extending it significantly. Estimating its impact precisely has not been an overriding concern - yet - due in part to the extensive sharing of brake components between regen-intensive battery-electric and hybrid vehicles, and their more friction-brake intensive internal combustion engine powered sibling. However, a multitude of factors are elevating the need for a more accurate estimation, including the emerging of dedicated electric vehicle architectures with opportunities for optimizing the friction brake design, a sharp focus on brake particulate emissions and the role of regenerative braking, a need to make design decisions for features such as corrosion protection for brake pad and pad slide components, and the emergence of driver-facing features such as Brake Pad Life Monitoring.

A linear parameter-varying model predictive control (LPVMPC) is proposed to enhance the longitudinal vehicle speed control of a gas-engine vehicle, with potential application in autonomous vehicles. To achieve this objective, an advanced vehicle dynamic model and a sophisticated fuel consumption model are derived, forming a control-oriented model for the proposed control system. The vehicle dynamic model accurately captures the motions of the tires and the vehicle body. The fuel consumption model incorporates new powertrain modes such as automatic engine stop/start, active fuel management, and deceleration fuel cut-off, etc. The performance of the proposed LPV-MPC is evaluated by comparing it to a PID controller. Both simulation tests and vehicle-in-the-loop tests demonstrate the superior performance of the proposed controller. The results indicate that the LPV-MPC provides improved longitudinal vehicle speed control and reduced fuel consumption.

Forward obstacles detection is one of the key tasks in the perception system of autonomous vehicles. The perception solution differs from the sensors and the detection algorithm, and the vision-based approaches are always popular. In this paper, an embedding fast obstacles detection algorithm is proposed to efficiently detect forward diverse obstacles from the image stream captured by the monocular camera. Specifically, our algorithm contains three components. The first component is an object detection method using convolution neural networks (CNN) for single image. We design a detection network based on shallow residual network, and an adaptive object aspect ratio setting method for training dataset is proposed to improve the accuracy of detection. The second component is a multiple object tracking method based on correlation filter for the adjacent images.

As the automotive industry vies to meet progressively more stringent global CO2 regulations in a cost-effective manner, electrified drive system cost and losses must be reduced. To this end, a parametric Drive Unit (DU) mechanical-loss model was developed to aid in the design and development of electrified propulsion systems, where the total propulsion system cost and DU losses can be directly linked (e.g., Hybrid Electric Vehicle (HEV) motor/inverter/engine content, or Battery Electric Vehicle (BEV) battery size). Many DUs for electrified propulsion systems are relatively “simple” drive systems, consisting of gears, bearings, shafts, lip seals, and an electric motor(s), but without clutches, high-pressure lube systems, or chains/belts as found in conventional automatic transmissions. The DU loss model described in this paper studies these simple DUs, with the mechanical losses dissected into 10 loss components.