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In this paper, we present a novel algorithm designed to accurately trigger the engine coolant flow at the optimal moment, thereby safeguarding gas-engines from catastrophic failures such as engine boil. To achieve this objective, we derive models for crucial temperatures within a gas-engine, including the engine combustion wall temperature, engine coolant-out temperature, engine block temperature, and engine oil temperature. To overcome the challenge of measuring hard-to-measure signals such as engine combustion gas temperature, we propose the use of new intermediate parameters. Our approach utilizes a lumped parameter concept with a mean-value approach, enabling precise temperature prediction and rapid simulation. The proposed engine thermal model is capable of estimating temperatures under various conditions, including steady-state or transient engine performance, without the need for extra sensors.

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 subsystem of front of dash (FOD) and instrument panel (IP) is a critical path to isolate the powertrain noise and road noise for vehicles. This subsystem mainly consists of sheet metal, dash mats, IP, and the components inside IP such as HVAC and wiring harness. To achieve certain level of cabin quietness, the sound transmission loss performance of this subsystem is usually used as a quantifier. In this paper, the sound transmission loss through the FOD and IP is investigated up to 10kHz, through both acoustic testing and numerical simulation. In the acoustic testing, the subsystem is cut from a vehicle and installed on the wall of two-rooms STL testing suite, with source room being reverberant and receiver room being anechoic. In the testing, various scenarios are measured to understand the contributions from different components.

General Motors (GM) is working towards a future world of zero crashes, zero emissions and zero congestion. It’s “Ultium” platform has revolutionized electric vehicle drive units to provide versatile yet thrilling driving experience to the customers. Three variants of traction power inverter modules (TPIMs) including a dual channel inverter configuration are designed in collaboration with LG Magna e-Powertrain (LGM). These TPIMs are integrated with other power electronics components inside Integrated power electronics (IPE) to eliminate redundant high voltage connections and increase power density. The developed power module from LGM has used state-of-the art sintering technology and double-sided cooled structure to achieve industry leading performance and reliability. All the components are engineered with high level of integration skills to utilize across TPIM variants.

With the advent of this new era of electric-driven automobiles, the simulation and virtual digital twin modeling world is now embarking on new sets of challenges. Getting key insights into electric motor behavior has a significant impact on the net output and range of electric vehicles. In this paper, a complete 3D CFD model of an Electric Motor is developed to understand its churning losses at different operating speeds. The simulation study details how the flow field develops inside this electric motor at different operating speeds and oil temperatures. The contributions of the crown and weld endrings, crown and weld end-windings, and airgap to the net churning loss are also analyzed. The oil distribution patterns on the end-windings show the effect of the centrifugal effect in scrapping oil from the inner structures at higher speeds. Also, the effect of the sump height with higher operating speeds are also analyzed.

A gasoline’s distillation profile is directly related to its hydrocarbon composition and the volatility (boiling points) of those hydrocarbons. Generally, the volatility profiles of U.S. market fuels are characterized using a very simple, low theoretical plate distillation separation, detailed in the ASTM D86 test method. Because of the physical chemistry properties of some compounds in gasoline, this simple still or retort distillation has some limitations: separating azeotropes, isomers, and heavier hydrocarbons. Chemists generally rely on chromatographic separations when more detailed and precise results are needed. High-boiling aromatic compounds are the primary source of particulate emissions from spark ignited (SI), internal combustion engines (ICE), hence a detailed understanding and high-resolution separation of these heavy compounds is needed.

Pulse Width Modulation or PWM has been widely used in traction motor control for electric propulsion systems. The associated switching noise has become one of the major NVH concerns of electric vehicles (EVs). This paper presents a multi-disciplinary study to analyze and validate current ripple induced switching noise for EV applications. First, the root cause of the switching noise is identified as high frequency ripple components superimposed on the sinusoidal three-phase current waveforms, due to PWM switching. Measured phase currents correlate well with predictions based on an analytical method. Next, the realistic ripple currents are utilized to predict the electro-magnetic dynamic forces at both the motor pole pass orders and the switching frequency plus its harmonics. Special care is taken to ensure sufficient time step resolution to capture the ripple forces at varying motor speeds.

Speaker performance in Acoustic Vehicle Alerting System (AVAS) plays a crucial role for pedestrian safety. Sound radiation from AVAS speaker has obvious directivity pattern. Considering this feature is critical for accurately simulating the exterior sound field of electrical vehicles. This paper proposes a new process to characterize the sound directivity pattern of AVAS speaker. The first step of the process is to perform an acoustic testing to measure the sound pressure radiated from the speaker at a certain number of microphone locations in a free field environment. Based on the geometry of a virtual speaker, the locations of each microphone and measured sound pressure data, an inverse method, namely the inverse pellicular analysis, is adopted to recover a set of vibration pattern of the virtual speaker surface. The recovered surface vibration pattern can then be incorporated in the full vehicle numerical model as an excitation for simulating the exterior sound field.

Zinc-based electrogalvanized (EG) and hot-dip galvanized (HDGI) coatings have been widely used in automotive body-in-white components for corrosion protection. The formability of zinc coated sheet steels depends on the properties of the sheet and the interactions at the interface between the sheet and the tooling. The frictional behavior of zinc coated sheet steels is influenced by the interfacial conditions present during the forming operation. Friction behavior has also been found to deviate from test method to test method. In this study, various lubrication conditions were applied to both bending under tension (BUT) test and a draw bead simulator (DBS) test for friction evaluations. Two different zinc coated steels; electrogalvanized (EG) and hot-dip galvanized (HDGI) were included in the study. In addition to the coated steels, a non-coated cold roll steel was also included for comparison purpose.

Accelerating product development cycles and incentives to reduce costs in product development are strong motivators to move to virtual development and validation processes. Challenges to moving to a virtual paradigm include a wealth of historical data and context for hardware tests, uncertainty over dependencies, and a lack of a clear path of transition to virtual methods. In this paper we will discuss approaches to understanding the value created by hardware tests and aligning that value to virtual processes. We will also discuss the need for a virtual context to be added to SAE J1739 [1] (DFMEA detection criteria), and how to create paths to maximize the value of virtual assessments. Finally, we will also discuss the cultural and organizational changes required to support.

As passenger vehicle design evolves and accelerates, the use of multi-body dynamics solvers has proven to be invaluable in the engineering workflow. MBD solvers allow engineers to build virtual vehicle models that can accurately simulate vehicle responses and calculate internal forces, which previously could only be assessed using physical prototype builds with hundreds of measurement transducers. Evaluation and selection of solvers within an engineering environment is inherently a multi-dimensional activity that can include ease of use, retention of previously developed expertise, accuracy, speed, and integration with existing analysis processes. We discuss here some of the challenges present in developing capability and accumulating data to support each of these criteria. Developing a pilot model that is capable of being applied to a comprehensive set of use cases, and then verifying those use cases, required significant project management activity.

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.

Designing power electronics to operate in harsh vehicle environments while meeting packaging requirements such as mass, volume, and power density, creates several challenges for their mechanical design. In this work, we concentrate on the power inverter module (PIM) which converts high voltage (HV) DC voltage power from the HV battery to AC power to drive the motor. The PIM main components are the power module, gate drive and the bulk capacitor. The sizing and selection of the bulk capacitor and power module depend on performance criteria and drive profiles in addition to operating temperatures. In this work, we share the main challenges of packaging components within the inverter. We then discuss best practices to ensure a robust mechanical design which meets inverter durability and reliability targets for an electric vehicle application. The main challenges discussed are bulk capacitor thermals, sealing, and Silicon Carbide (SiC) packaging.

The front camera module is a fundamental component of a modern vehicle’s active safety architecture. The module supports many active safety features. Perception of the road environment, requests for driver notification or alert, and requests for vehicle actuation are among the camera software’s key functions. This paper presents a novel method of testing these functions virtually. First, the front camera module software is compiled and packaged in a Docker container capable of running on a standard Linux computer as a software in the loop (SiL). This container is then integrated with the active safety simulation tool that represents the vehicle plant model and allows modeling of test scenarios. Then the following simulation components form a closed loop: First, the active safety simulation tool generates a video data stream (VDS). Using an internet protocol, the tool sends the VDS to the camera SiL and other vehicle channels.

Battery Electric Vehicles (BEVs) are becoming more competitive day by day to achieve maximum peak power and energy requirement. This poses challenges to the design of Thermal Interface Material (TIM) which maintains the cell temperature and ensure retention of cell and prevent electrolyte leak under different crash loads. TIM can be in the form of adhesives, gels, gap fillers. In this paper, TIM is considered as structural, and requires design balance with respect to thermal and mechanical requirements. Improving structural strength of TIM will have negative impact on its thermal conductivity; hence due care needs to be taken to determine optimal strength that meets both structural and thermal performance. During various crash conditions, due to large inertial force of cell and module assembly, TIM is undertaking significant loads on tensile and shear directions. LS-DYNA® is used as simulation solver for performing crash loading conditions and evaluate structural integrity of TIM.

Use of electronic systems in the vehicles is increasing day by day. As Electronic Control Modules (ECMs) become a large part of the vehicle, automotive designers need to take diligent decision of selecting electrical and electronic components. Selecting these components for ECM depends on four major factors: meeting stringent vehicle requirements, performance over the lifespan, robustness/reliability and cost. There is always an urge of reducing the cost of the ECM, but robustness of the controller module must not be compromised. One electrical or electronic component failure or false fault detection not only increases warranty cost but may also stall the vehicle, and interrupts customer’s daily routine creating dissatisfaction. This paper emphasizes on the importance of understanding worst-case operating scenarios considering component tolerances over the operating range, datasheet, and impact of tolerances on performance and fault detection.

Elastomers are widely used in many automotive components such as seals, gaskets etc., for their hyperelastic properties. They can undergo large strain and can return to their original state with no significant deformation making them suitable for energy dissipation applications. Most common testing procedures include uniaxial tension, pure shear, biaxial tension and volumetric compression under quasi-static loading conditions. The results from these tests are used to generate material models for different finite element (FE) solvers, such as LS-DYNA. Commonly used material models for elastomers in LS-DYNA are the Ogden Material Model (MAT77), which uses parameter-based approach and the Simplified Rubber Material Model (MAT181), which uses tabulated input data. Prediction of rate dependent behavior of elastomers is gaining interest as, for example, during a crash simulation the components undergo impact under different strain rates.

The validation of brake discs has remained, to this day, heavily reliant on “Thermal Abuse” or “Thermal Cracking” type testing, with many procedures so dated that most engineers active in the industry today cannot even recall the origin of the test. These procedures - of which there are many variants - all share the trait of greatly accelerating durability testing by performing repeated high power (high speed and high deceleration) brake applies to drive huge temperature gradients and internal stress, and often allowing the disc to get very hot, to where the strength of the material from which the disc is constructed is significantly degraded. There is little debate about whether these procedures work; by and large disc durability issues in the field are extremely rare.

Euro 7/VII regulations are currently under discussion and are expected to be the last big regulatory step in Europe. From available documentation, it is clear the aim of further regulating the extended conditions of use which are still responsible of high emission events (e. g. cold start or altitude) as well as regulating secondary emissions such as NH3, N2O, CH4, Aldehydes (HCHO). Even if not completely fixed yet, the EU7 limits will be challenging for internal combustion engines and even more for Diesel. Despite a consistent reduction of market share, Diesel engines are expected to remain a significant portion in certain sectors such as Heavy duty (HD) and Light-commercial vehicle (LCV) for some decades. In order to reach the new limits being proposed, besides minimizing engine-out emissions, Diesel powertrain will need an aftertreatment system able to work at very high efficiency right after engine start and in almost every working and environmental condition.

Thermal cabin comfort is the largest consumer of battery energy second only to propulsion in Battery Electric Vehicles (BEV’s). Accurate prediction of thermal comfort in the vehicle cabin with fast turnaround times will allow engineers to study the impact of various thermal comfort technologies and develop energy efficient Heating, Ventilation and Air Conditioning (HVAC) systems. In this study a novel data-driven model based on physics-guided Sparse Identification of Nonlinear Dynamics (SINDy) method was developed to predict Equivalent Homogeneous Temperature (EHT), Mean Radiant Temperature (MRT) and cabin air temperature under transient conditions and drive cycles. EHT is a recognized measure of the total heat loss from the human body that can be used to characterize highly non-uniform thermal environments such as a vehicle cabin. The SINDy model was trained on drive cycle data from Climatic Wind Tunnel (CWT) for a representative Battery Electric Vehicle.