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The automotive industry is facing many significant challenges that go far beyond the design and manufacturing of automobile products. Connected, autonomous and electric vehicles, smart cities, urbanization and the car sharing economy all present challenges in a fast-changing environment which the automotive industry must adapt to. Cars no longer are just standalone systems, but have become constituent systems (CS) in larger System of Systems (SoS) context. This is reflected in the emergence of several acronyms such as vehicle-to-everything (V2X), vehicle-to-vehicle (V2V), vehicle-to-infrastructure (V2I), and vehicle-to-grid (V2G) expressions. System of Systems are defined systems of interest whose elements (constituent systems) are managerially and operationally independent systems. This interoperating and/or integrated collection of constituent systems usually produce results unachievable by the individual systems alone, for example the use of car batteries as virtual power plants.

Vehicle manufacturers conduct tests to develop crash sensing system calibrations. Ditch fall-over is one of a suite of laboratory tests used to develop rollover sensing calibrations that can trigger deployment of safety devices like roof rail airbags and seat belt pretensioners. The ditch fall-over test simulates a flat road followed by a ditch on one side of the road. The vehicle heads into the ditch and the driver applies swift steer input once the ditch slope is sensed. Typically, the steer input is applied when the two down-slope wheels on the ditch side enter the ditch. Multi-Body Dynamics (MBD) software can be used for virtual simulation of these test events. Conventionally in simulations, the vehicle-model is run without steer input and the marking line crossing time is observed/manually recorded from observation of simulation video. This recorded time is used to apply the steer input and the full event is then re-simulated.

Hybridization is a mainstream technology for automobiles, and its application is rapidly expanding in other fields. Marine propulsion is one such field that could benefit from electrification of the powertrain. In particular, for boats to sail in enclosed waterways, such as harbors, channels, lagoons, a pure electric mode would be highly desirable. The main challenge to accomplish hybridization is the additional weight of the electric components, in particular the batteries. The goal of this project is to replace a conventional 4-stroke turbocharged Diesel engine with a hybrid powertrain, without any penalty in terms of weight, overall dimensions, fuel efficiency, and pollutant emissions. This can be achieved by developing a new generation of 2-Stroke Diesel engines, and coupling them to a state-of-the art electric system. For the thermal units, two alternative designs without active valve train are considered: opposed piston and loop scavenged engines.

With the increasing content of electronics in automobiles and faster development times, it is essential that electronics hardware design and vehicle electrical architecture is done early and correctly. Today, the first designs are done in the electronic format with circuit and CAD design tools. Once the initial design is completed, several iterations are typically conducted in a “peer review” methodology to incorporate “best practices” before actual hardware is built. Among the many challenges facing electronics design and integration is electromagnetic compatibility (EMC). Success in EMC starts at the design phase with a relevant “lessons learned” data set that encompasses component technology content, schematic and printed circuit board (PCB) layout, and wiring using computer aided engineering (CAE) tools.

General Motors (GM) vehicle design operations group has envisioned that all designers and Design Engineers (DEs) should be able to analyze simple and single components and produce robust subsystem parts to support full vehicle system analysis. This vision is achieved by developing the Smart Simulation Tool (SST) within the Siemens NX CAD system. This tool empowers the designers to take charge of simple parts and produce high quality parts first time. This tool will also make both design and engineering analysis organizations at General Motors more efficient and productive. This paper describes the Smart Simulation Tool that was developed to automate the pre and post processing tasks of the Siemens NX Advanced Simulation process. Generally, the simulation process consumes a lot of designer’s time for building the Finite Element Analysis (FEA) models, typically one to two hours and is very tedious and has the potential for errors.

Turbochargers are widely employed in internal combustion engines, in both, diesel and gasoline vehicle, to boost the power without any extra fuel usage. Turbocharger comes in different sizes based upon the boost pressure to increase. Capacity of turbocharger are available in great range in the market which are designed to match the requirement. From structural point of view, key component of an automotive turbocharger is rotor. This rotor consists of compressor wheel, turbine wheel, shaft and bearing (journal/ball) mainly. In industries, design & development of turbocharger rotor for its dynamic characteristics is done using virtual engineering technique (Computer Aided Engineering). Multibody dynamic (MBD) analysis simulation is one of the best approaches which is used to study the rotor in great details. In this current MBD procedure fluid-structure interaction problem is solved by modelling oil film in the journal bearing and solving it using “Reynolds equation”.

As fossil fuels dwindle and more electric vehicles enter the market, there is an opportunity to reevaluate the standard brake system. This paper will discuss and compare the differences in brake system sizing between a non-regenerative braking internal combustion engine vehicle and a dedicated battery electric vehicle with regenerative braking. It will use a model derived from component dynamometer testing and vehicle test data of a mid-size production vehicle. The model will be modified for the mass and regenerative braking capabilities of a battery electric vehicle. The contribution of regenerative braking energy will be analyzed and compared to show its impact on component sizing, thermal sizing, and lining life. The detailed design study will calculate the parameters for caliper, rotor design, actuation, etc., that are optimized for 100% regen enabled vehicles.

The purchase of a new automobile is unquestionably a significant investment for most customers, and with this recognition, comes a correspondingly significant expectation for quality and reliability. Amongst automotive systems -when it comes to considerations of reliability - the brakes (perhaps along with the tires) occupy a rarified position of being located in a harsh environment, subjected to continuous wear throughout their use, and are critical to the safe performance of the vehicle. Maintenance of the brake system is therefore a fact of life for most drivers - something that almost everyone must do, yet given the potentially considerable expense, it is something that of great benefit to minimize.

Remote Function Actuator (RFA) systems are widely used as the standard solution for conveniently accessing vehicles by remote control. To accelerate product development cycles and reduce engineering costs of physical test, a computer aided engineering (CAE) method has been developed to predict transmission range of the RFA system. Firstly, the detailed computational electromagnetic (CEM) models of the transmitting and receiving antennas were developed. Secondly, the articulated human model and the full vehicle meshed model were introduced to the CEM models to reflect the physical test environment. Lastly, the RFA system range model was built by including both the key fob held by an articulated human body and RFA module installed in the fully meshed vehicle. The transmission range could be extracted when the simulated received power reached the receiving sensitivity of the RFA module.

This paper proposes a model-based “Cascaded Dual Extended Kalman Filter” (CDEKF) for combined vehicle state estimation, namely, tire vertical forces and parameter identification. A sensitivity analysis is first carried out to recognize the vehicle inertial parameters that have significant effects on tire normal forces. Next, the combined estimation process is separated in two components. The first component is designed to identify the vehicle mass and estimate the longitudinal forces while the second component identifies the location of center of gravity and estimates the tire normal forces. A Dual extended Kalman filter is designed for each component for combined state estimation and parameter identification. Simulation results verify that the proposed method can precisely estimate the tire normal forces and accurately identify the inertial parameters.

Seat lateral support is often talked about as a design parameter, but usually in terms of psychological perception. There are many difficulties in quantifying lateral support mechanically to the engineering teams: Anthropometric variation causes different people to interact with the seat in different places and at different angles, BPD studies are usually planar and don’t distinguish between horizontal support and vertical resistance to sinking in, most mechanical test systems are typically single-DOF and can’t apply vertical and horizontal loads concurrently, and there is scant literature describing the actual lateral loads of occupants. In this study, we characterize the actual lateral loading on example seating from various sized/shaped occupants according to dynamic pressure distribution. From this information, a six-DOF load and position control test robot (KUKA OccuBot) is used to replicate that pressure distribution.

The main objective of this work is to present an adjoint-based methodology to address combined optimization of drag force and cooling flow rate of an industrial vehicle. In order to cope with cooling effect, the volumetric flow rate is treated through a newly introduced cost function and the corresponding adjoint source term is derived. Also an alternative strategy is presented to tackle aerodynamic vehicle design improvement that relies on a so-called indirect force computation. The overall optimization is treated as a Multi-Objective problem and an original approach, called Optimize Both Favor One (OBFO), is introduced that allows selective emphasis on one or another objective without resorting to artificial cost function balancing. Finally, comparative results are presented to demonstrate the merit of the proposed methodology.

Hybrid and electric vehicles utilize high power electric motors to propel the vehicle requiring a significant level of electric current to travel between various modules such as energy storage devices, power inverter modules, energy charging modules, and the motors themselves. This electric current creates magnetic fields around the devices themselves and wiring that delivers this current between devices within the vehicle. These devices and wiring exist throughout the vehicle and can even exist near vehicle occupants, which has prompted investigations looking into the short term biological effect these non-ionizing fields can have on the human body. The findings from these investigations have been published by organizations such as the International Commission on Non-Ionizing Radiation Protection (ICNIRP), and some nations have passed laws regulating the magnetic and electric field exposure to vehicle occupants.

Automotive liftgate latches have been subject to regulation for minimum strength and inertial resistance requirements since the late 1990’s in the US and globally since the early 2000’s, possibly due to liftgate ejections stemming from the first generation Chrysler minivans which employed latches that were not originally designed with this hazard in mind. Side door latches have been regulated since the 1960’s, and the regulation of liftgate, or back door latches, have been based largely on side door requirements, with the exception of the orthogonal test requirement that is liftgate specific. Based on benchmarking tests of liftgate latches, most global OEM’s design their latches to exceed the minimum regulatory requirements. Presumably, this is based on the need to keep doors closed during crashes and specifically to do so when subjected to industry standard tests.

The world is moving towards E-mobility solutions and Battery Electric Vehicles (BEVs) are the main enabler towards it. Li-ion cells are the fundamental building block of any BEVs. There are three common types of Li-ion cell design i.e., cylindrical cells, Prismatic Cells and Pouch cells. Ensuring safety of BEVs are critical to gain customer trust and acceptance over Internal Combustion Engine (ICE) vehicles. EV fire is found to be one of the major concerns related to using higher energy batteries. During a crash event, Post-Crash Electrical Integrity of the BEV is to be ensured and hence primary focus is on mitigation of Li-ion cell internal short circuit. It has been seen in prior published articles that cell internal short circuit can be triggered by physical intrusion of cell. This paper primarily focusses on simulating the mechanical behavior of cylindrical cell under various crush conditions.

Fatigue failure is one of the major failure modes for internal combustion engines, especially with reduction in engine size and increase in combustion pressure and operating temperature. Dynamometer tests are devised to ensure engine durability for high and low cycle fatigue. With the advent of CAE technology, the dynamometer test behavior can be simulated using CAE analysis and engine durability can be assessed. The data generated in CAE analyses can be used to predict failure of the engines or future engine design modifications. The present paper has two parts - first is running finite element analysis (FEA) to get stress, strain data and running high cycle fatigue analysis to get safety factors and second is creating a predictive tool to assess failures using data from the first part as inputs. Using advancements in the field of machine learning, the paper presents use of support vector machine (SVM) algorithm to predict failure of the engine based on inputs.

Adaptive cruise control is an advanced vehicle technology that is unique in its ability to govern vehicle behavior for extended periods of distance and time. As opposed to standard cruise control, adaptive cruise control can remain active through moderate to heavy traffic congestion, and can more effectively reduce greenhouse gas emissions. Its ability to reduce greenhouse gas emissions is derived primarily from two physical phenomena: platooning and controlled acceleration. Platooning refers to reductions in aerodynamic drag resulting from opportunistic following distances from the vehicle ahead, and controlled acceleration refers to the ability of adaptive cruise control to accelerate the vehicle in an energy efficient manner. This research calculates the measured greenhouse gas emissions benefit of adaptive cruise control on a fleet of 51 vehicles over 62 days and 199,300 miles.

General Motors’ 3rd generation eAssist propulsion systems build upon the experience gained from the 2nd generation 115v system and the 1st generation 36v system. Extensive architectural studies were conducted to optimize the new eAssist system to maintain the performance and fuel economy gains of the 2nd generation 115v system while preserving passenger and cargo space, and reducing cost. Three diverse vehicle applications have been brought to production. They include two similar pickup trucks with 5.3 liter V8 engines and 8 speed transmissions, a 4-door passenger car with 2.5 liter 4 cylinder normally aspirated gasoline engine and a 6-speed automatic transmission, and a crossover SUV with a 2.0-liter turbocharged engine and 9 speed transmission. The key electrification components are a new water cooled induction motor/generator (MG), new water cooled power electronics module, and two major variants of 86v lithium ion battery packs.

DC fast charging (DCFC) also referred to as L3 charging, is the fastest charging technology to replenish the drivable range of an electric vehicle. DCFC provides the convenience of faster charging time compared to L1 and L2 at the expense of potentially increased battery health degradation. It is known to accelerate battery capacity fade leading to reduced range and lifetime of the EV battery. While there are active efforts and several means to reduce the downsides of DCFC at cell chemistry level, this trade-off is still an important consideration for most battery cells in automotive propulsion applications. Since DCFC is a customer driven technology, informing drivers of the trade-off of each DCFC event can potentially result in better outcomes for the EV battery life. Traditionally, the driver is advised to limit DCFC events without providing quantifiable metrics to inform their decisions during EV charging.

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.