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Due to the recent progress in electrification, lithium-ion batteries have been widely used for electric and hybrid vehicles. Lithium-ion batteries exhibit high energy density and high-power density which are critical for vehicle development with high driving range enhanced performance. However, high battery temperature can negatively impact the battery life, performance, and energy delivery. In this paper, we developed and applied an analytical algorithm to estimate battery life-based vehicle level testing. A set of vehicle level tests were selected to represent customer duty cycles. Thermal degradation models are applied to estimate battery capacity loss during driving and park conditions. Due to the sensitivity of Lithium-Ion batteries to heat, the effect of high ambient temperatures throughout the year is considered as well. The analysis provides an estimate of the capacity loss due to calendar and cyclic effects throughout the battery life.

In this paper, a control strategy for state of charge (SOC) allocation using navigation data for Hybrid Electric Vehicle (HEV) propulsion systems is proposed. This algorithm dynamically defines and adjusts a SOC target as a function of distance travelled on-line, thereby enabling proactive management of the energy store in the battery. The proposed approach incorporates variances in road resistance and adheres to geolocation constraints, including ultra-low emission zones (uLEZ). The anticipated advantages are particularly pronounced during scenarios involving extensive medium-to-long journeys characterized by abrupt topological changes or the necessity for exclusive electric vehicle (EV) mode operation. This novel solution stands to significantly enhance both drivability and fuel economy outcomes.

During driving conditions, when it is needed to transition from Electric Vehicle (EV) to Hybrid Vehicle operation, synchronization of the engine with the shaft and transmission is essential to enable clutch engagement and, subsequently, providing engine power to the wheels. Challenges arise when the engine must generate power to move itself and cannot rely on electric motors for precision. Cost-effective hybrid vehicle propulsion architectures which utilize small 12V belt-starter generators (BSGs) to initiate engine activation are inherently affected. In these situations, a speed profile that balance rapid response and control effort while considering system limitations to mitigate undesirable overshoots and delays, is required. This paper presents a Linear Quadratic Integral (LQI) approach to formulate a speed reference profile that ensures optimal engine behavior.

Connectivity in ground vehicles allows vehicles to share crucial vehicle data, such as vehicle acceleration and speed, with each other. Using sensors such as radars and lidars, on the other hand, the intravehicular distance between a leader vehicle and a host vehicle can be detected. Cooperative Adaptive Cruise Control (CACC) builds upon ground vehicle connectivity and sensor information to form convoys with automated car following. CACC can also be used to improve fuel economy and mobility performance of vehicles in the said convoy. In this paper, a CACC system is presented, where the acceleration of the lead vehicle is used in the calculation of desired vehicle speed. In addition to the smooth car following abilities, the proposed CACC also has the capability to calculate a speed profile for the ego vehicle that is fuel efficient, making it an Ecological CACC (Eco-CACC) model.

With the proliferation of electric vehicles in the market, it has become important for Automotive OEMs (Original Equipment Manufacturers) to focus on delivering a higher driving range while also maximizing performance. One approach OEMs are actively considering in meeting this goal is to include a secondary drive axle disconnect into the powertrain which has the potential to improve the overall driving range by about 6-8.3% [4]. This paper outlines the need for a novel controls architecture to make the Powertrain controls software modular and to reduce the development time needed to provide robust powertrain control software. To do this, the electrified powertrain torque controls at STELLANTIS NV takes a decentralized controls architecture approach, by separating the axle disconnect controls subsystem (ADCS) from the primary path of torque controls. The ADCS takes in information such as the desired axle state and controls the axle disconnect actuators to achieve that state.

Metal cutting/machining is a widely used manufacturing process for producing high-precision parts at a low cost and with high throughput. In the automotive industry, engine components such as cylinder heads or engine blocks are all manufactured using such processes. Despite its cost benefits, manufacturers often face the problem of machining chips and cutting oil residue remaining on the finished surface or falling into the internal cavities after machining operations, and these wastes can be very difficult to clean. While part cleaning/washing equipment suppliers often claim that their washers have superior performance, determining the washing efficiency is challenging without means to visualize the water flow. In this paper, a virtual engineering methodology using particle-based CFD is developed to address the issue of metal chip cleanliness resulting from engine component machining operations. This methodology comprises two simulation methods.

Common aerodynamic research models have been used in aerodynamic research throughout the years to assist with the development and correlation of new testing and numerical techniques, in addition to being excellent tools for gathering fundamental knowledge about the physics around the vehicle. The generic truck utility (GTU) was introduced by Woodiga et al. [1] in 2020 following successful adoption of the DrivAer (Heft et al. [2]) by the automotive aerodynamics community with the goal to capture the unique flow fields created by pickups and large SUVs. To date, several studies have been presented on the GTU (Howard et. al 2021 [3], Gleason, Eugen 2022 [4]), however, with the increasing prevalence of electric vehicles (EVs), the authors have created additional GTU configurations to emulate an EV-style underbody for the GTU.

This work represents an advanced engineering research project partially funded by the U.S. Department of Energy (DOE). Ford Motor Company, FEV North America, and Oak Ridge National Laboratory collaborated to develop a next generation boosted spark ignited engine concept. The project goals, specified by the DOE, were 23% improved fuel economy and 15% reduced weight relative to a 2015 or newer light-duty vehicle. The fuel economy goal was achieved by designing an engine incorporating high geometric compression ratio, high dilution tolerance, low pumping work, and low friction. The increased tendency for knock with high compression ratio was addressed using early intake valve closing (EIVC), cooled exhaust gas recirculation (EGR), an active pre-chamber ignition system, and careful management of the fresh charge temperature.

The rise of greenhouse gas emissions has reached historic levels, with 37 billion tons of CO2 released into the atmosphere in 2018 alone. In the European Union, 32% of these emissions come from transportation, with 73.3% of that percentage coming from vehicles. To address this problem, solutions such as cleaner fuels and more efficient engines are necessary. Artificial Intelligence can also play a crucial role in climate analysis and verification to move towards a more sustainable future. By utilizing connected vehicle data, automakers can analyze real-time vehicle performance data to identify opportunities for improvement and reduce carbon emissions. This approach benefits the environment, improves vehicle quality, and reduces engineering work time, making it a win-win solution. Connected vehicle data offers a wealth of information on vehicle performance, such as fuel consumption and carbon emissions.

In recent years, the automotive industry has seen an exponential increase in the replacement of mechanical components with electronic-controlled components or systems. engine, transmission, brake, exhaust gas recirculation (EGR), lighting, driver-assist technologies, etc. are all monitored and/or controlled electronically. Connected vehicles are increasingly being used by Original Equipment Manufacturers (OEMs) to collect and transmit vehicle data in real-time via the use of various sensors, actuators, and communication technologies. Vehicle telematics devices can collect and transmit data about the vehicle location, speed, fuel efficiency, State Of Charge (SOC), auxiliary battery voltage, emissions, performance, and more. This data is sent over to the cloud via cellular networks, where it can be processed and analyzed to improve their products and services by automotive companies and/or fleet management.

In the present work, five surrogate components (n-Hexadecane, n-Tetradecane, Heptamethylnonane, Decalin, 1-Methylnaphthalene) are proposed to represent liquid phase of diesel fuel, and another different five surrogate components (n-Decane, n-Heptane, iso-Octane, MCH (methylcyclohexane), Toluene) are proposed to represent vapor phase of diesel fuel. For the vapor phase, a 5-component surrogate chemical kinetic mechanism has been developed and validated. In the mechanism, a recently updated H2/O2/CO/C1 detailed sub-mechanism is adopted for accurately predicting the laminar flame speeds over a wide range of operating conditions, also a recently updated C2-C3 detailed sub-mechanism is used due to its potential benefit on accurate flame propagation simulation. For each of the five diesel vapor surrogate components, a skeletal sub-mechanism, which determines the simulation of ignition delay times, is constructed for species C4-Cn.

Automotive Heating Ventilation and Air Conditioning (HVAC) system is essential in providing the thermal comfort to the cabin occupants. The HVAC noise which is typically not the main noise source in IC engine vehicles, is considered to be one of the dominant sources inside the electric vehicle cabin. As air is delivered through ducts and registers into the cabin, it will create an air-rush/broadband noise and in addition to that, any sharp edges or gaps in flow path can generate monotone/tonal noise. Noise emanating from the HVAC system can be reduced by optimizing the airflow path using virtual tools during the development stage. This paper mainly focuses on predicting the noise from the HVAC ducts and registers. In this study, noise simulations were carried-out with ducts and registers. A Finite Volume Method (FVM) based 3-dimensional (3D) Computational Fluid Dynamics (CFD) solver was used for flow as well as acoustic simulations.

This is an extension of simple fuel consumption modeling toward HEV. Previous work showed that in urban driving the overhead of running an ICEV engine can use as much fuel as the traction work. The bidirectional character and high efficiency of electric motors enables HEVs to run as a BEV at negative and low traction powers, with no net input from the small battery. The ICE provides the net work at higher traction powers where it is most efficient. Whereas the network reduction is the total negative work times the system round-trip efficiency, the reduction in engine running time requires knowledge of the distribution of traction power levels. The traction power histogram, and the work histogram derived from it, provide the required drive cycle description. The traction power is normalized by vehicle mass, so that the drive trace component becomes invariant, and the road load component nearly invariant to vehicle mass.

The automotive industry is moving towards larger SUVs and also electrification is a need to meet the carbon neutrality target. As a result, we see an increase in overall gross vehicle weight (GVW), with the additional weight coming from the HV battery pack, electric powertrain, and other electrical systems. Tow-eye is an essential component that is provided with every vehicle to use for towing during an emergency vehicle breakdown. The tow-eye is usually connected to the retainer/sleeve available in the bumper system and towed using the recovery vehicle or other car with towing provision. Therefore, the tow-eye should meet the functional targets under standard operating conditions. This study is mainly for cars with bumper and tow-eye sleeves made of aluminum which is used in the most recent development of vehicles for weight-saving opportunities. Tow-eye systems in aluminum bumpers are designed to avoid any bending or buckling of the sleeve during towing for whatever the GVW loads.

Recently, the automotive industry has experienced rapid growth in powertrain electrification, with more and more battery electric vehicles (BEV) and hybrid electric vehicles being launched. Lithium-ion batteries play an important role due to their high energy capacity and power density, however they experience high heat generation in their operation, and if not properly cooled it can lead to serious safety issues as well as lower performance and durability. In that way, good prediction of a battery behavior is crucial for successful design and management. This paper presents a 1D electrochemical model development of a 144 Ah prismatic rolled cell using the GT-Autolion software with a pseudo 2D approach. The model correlation is done at cell level comparing model results and test data of cell open circuit voltage at different temperatures and voltage and temperature profile under different C-rates and ambient temperatures.

Lithium-ion batteries (LIBs) have been used as the main power source for Electric vehicles (EVs) in recent years. The mechanical behavior of LIBs subject to crush loading is crucial in assessing and improving the impact safety of battery systems and EVs. In this work, a detailed 3D finite element model for a commercial vehicle battery was built, in order to better understand battery failure behavior under various loading conditions. The model included the major components of a prismatic battery jellyroll, i.e., cathodes, anodes, and separators. The models for these components were validated against the corresponding material coupon tests (e.g., tension and compression). Then the components were integrated into the cell level model for simulation of jellyroll loading and damage behavior under three types of compressive indenter loading: (1) Flat-end punch, (2) Hemispherical punch and (3) Round-edge wedge. The comparisons showed reasonable agreement between modeling and experiments.

When manufacturing the stators in EV motors, stator wires are first coated with a layer of resin to provide primary insulation. After winding, impregnating varnish fills all voids within the windings and between the windings and lamination. In addition to electrically insulating the copper wires, another function of the varnish fill is to mechanically secure the copper wires from movement. The process is not complicated in terms of physics. In essence, the mechanics of the varnish flow is the balance of inertia force, viscous force, gravity and surface tension. However, understanding the fluid dynamics of the varnish flow is critical to predicting the quality of the varnish fill, which has a tremendous impact on motor performance. With the advancement of computational fluid dynamics (CFD), the industry can benefit greatly if the varnish trickling process can be tuned, without physical tryouts, to achieve optimal fill.

As the automotive industry is quickly changing towards electric vehicles, we can highlight the importance of aerodynamics and its critical role in reaching extended battery ranges for electric cars. With all new smooth underbodies, a lot of attention has turned into the effects of rim designs and tires brands and the management of these tire wakes with the vehicle. Tires are one of the most challenging areas for aerodynamic drag prediction due to its unsteady behavior and rubber deformation. With the simulation technologies evolving fast regarding modeling spinning tires for aerodynamics, this paper takes the prior work and data completed by the authors and investigates the impact on the flow fields and aerodynamic forces using the most recent developments of an Immerse Boundary Method (IBM). IBM allows us to mimic realistically a rotating and deformed tire using Lattice Boltzmann methods.

As more electric vehicles (BEV, HEV, PHEV, etc.) are adopted in the upcoming decades, it is becoming increasingly important to conduct vehicle-level thermal simulations under different drive-cycle conditions while incorporating the various subsystem thermal losses. Thermal management of the various heat sources in the vehicle is essential both in terms of ensuring passenger safety as well as maintaining all the subsystems within their corresponding safe temperature limits. It is also imperative that these thermal simulations include energy consumption prediction, while considering the effect of battery degradation both in terms of increased thermal losses as well as reduction in the vehicle’s range. For this purpose, a three-dimensional transient thermal analysis framework was coupled with an electrochemical P2D-based battery model and a vehicle dynamics model to test different scenarios and their effect on a hybrid vehicle’s range and the lithium-ion battery life.

Owing to climate change issues caused by global warming, the role of alternative fuels, such as low-carbon and non-carbon fuels, is becoming increasingly important, particularly in the transportation sector. Therefore, hydrogen has emerged as a promising fuel for internal combustion engines because it does not emit carbon dioxide. Direct injection is mandatory for hydrogen-based internal combustion engines to mitigate backfires and low energy density. However, there is a lack of measurement of the equivalence ratio methodology because hydrogen has a higher diffusion rate than conventional fuels. The objective of this research is a feasibility study of laser-induced breakdown spectroscopy (LIBs) for measuring the equivalence ratio. The second harmonic ND-YAG laser was implemented to induce the atomic emission of hydrogen via the breakdown phenomenon. Simultaneously, the hydrogen jet structure was visualized in a constant volume vessel using Schlieren imaging.