Search Results

Noise, vibration and harshness (NVH) is one of the most important performance evaluation aspect of electric motors. Among the different causes of the NVH issues of electrical drives, the high-frequency spatial and temporal harmonics of the electrical drive system is of great importance. To reduce the tonal noise of the electric motors, harmonic injection methods can be applied. However, a lot of the existing related work focuses more on improving the optimization process of the parameter settings of the injected current/flux/voltage, which are usually limited to some specific working conditions. The applicability and effectivity of the algorithm to the whole frequency/speed range are not investigated. In this paper, a multi-domain pipeline of harmonic injection controller design for a permanent magnet synchronous motor (PMSM) is proposed.

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.

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.

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.

Gasoline particulate filters (GPF) have become a standard aftertreatment component in Europe, China, and since recently, India, where particulate emissions are based on a particle number (PN) standard. The anticipated evolution of regulations in these regions towards future EU7, CN7, and BS7 standards further enhances the needs with respect to the filtration capabilities of the GPFs used. Emission performance has to be met over a broader range in particle size, counting particles down to 10nm, and over a broader range of boundary conditions. The requirements with respect to pressure drop, aiming for as low as possible, and durability remain similar or are also enhanced further. To address these future needs new filter technologies have been developed. New technologies for uncatalyzed GPF applications have been introduced in our previous publications.

Plug-In Hybrid Vehicles (PHEV) have been of significant importance recently to comply with future CO2 and pollutant emissions limit. However, performance of these vehicles is closely related to the energy management strategy (EMS) used to ensure minimum fuel consumption and maximize electric driving range. While conventional EMS concepts are developed to operate in wide range of scenarios, this approach could potentially compromise the fuel consumption benefit due to the omission of route and traffic information. With the advancements in the availability of real-time traffic, navigation and driving route information, the EMS can be further optimized to extract the complete potential of a PHEV. In this context, this paper presents application of predictive energy management (PEM) functionalities combined with information such as live traffic data to reduce the fuel consumption for a P1/P3 configuration PHEV vehicle.

Pre-ignition in a boosted spark-ignition engine can be triggered by several mechanisms, including oil-fuel droplets, deposits, overheated engine components and gas-phase autoignition of the fuel-air mixture. A high pre-ignition resistance of the fuel used mitigates the risk of engine damage, since pre-ignition can evolve into super-knock. This paper presents the pre-ignition propensities of 11 RON 89-100+ gasoline fuel blends in a single-cylinder research engine. Albeit the addition of two high-octane components (methanol and reformate) to a toluene primary reference fuel improved the pre-ignition resistance, one high-RON fuel experienced runaway pre-ignition at relatively low boost pressure levels. A comparison of RON 96 blends showed that the fuel composition can affect pre-ignition resistance at constant RON.

The innovation and application of new technologies in battery electric vehicle (BEV) development continues to be a key objective of the automotive industry. One such area of development is glazing designs that reduce transmission of noise into vehicle interiors. Highly asymmetric laminated front side lites that consist of thick soda lime glass exterior plies laminated with thinner ion exchanged interior plies with acoustic polyvinyl butyral interlayers offer substantially reduced noise transmission compared to industry standard monolithic front side lites. These asymmetric laminate designs also provide additional benefits of improved toughness and penetration resistance. This paper documents a study that uses a systematic test-based approach to understand the sensitivity of interior vehicle noise behavior to changes in acoustic attenuation driven by installation of asymmetric laminated glass front side lites.

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.

The charge air cooler (CAC), which is placed between the compressor and the engine intake manifold (IM), is an important component in a turbocharged engine. It is essential to capture the temperature change, the pressure drop or the acoustical wave behavior of the charge air cooler in the one-dimensional(1D) simulation model for the predictive accuracy of engine performance and intake noise. In this paper, the emphasis is on the acoustic modeling of an intake manifold and charge air cooler assembly for the low frequency engine intake order noise. In this assembly, the core of the charge air cooler is embedded in the plenum of the intake manifold. The modeling and correlation process is comprised of three steps. First, the charge air cooler core is removed from the intake manifold and put into a rectangular box matching its envelope with a single air inlet and outlet, thereby simplifying the complex shape of the manifold with the different runner components.

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.

Many chassis and powertrain components in the transportation and automotive industry experience multi-axial cyclic service loading. A thorough load-history leading to durability damage should be considered in the early vehicle production steps. The key feature of rubber fatigue analysis discussed in this study is how to define local critical location strain time history based on nominal and complex load time histories. Material coupon characterization used here is the crack growth approach, based on fracture mechanics parameters. This methodology was utilized and presented for a truck engine mount. Temperature effects are not considered since proving ground (PG) loads are generated under isothermal high temperature and low frequency conditions without high amounts of self-heating.

Vibration shaker testing is a great tool of validating the vibration fatigue performance of automotive components & systems. However, the representative vibration schedule requires a pre-knowledge of the acceleration history for the test object, which usually is not available until the later development phase of a vehicle program when physical properties are available. Sometimes, a generic vibration schedule developed from the worst-case loading profiles are used with risk of lacking correlation with later full vehicle durability test such as Road Test Simulator (RTS) or Proving Ground (PG) road test due to the higher loading amplitude. This paper proposes a virtual accelerometer approach to collect acceleration responses of a component from a virtual vehicle model. First, a multiple body dynamic model will be produced for virtual load calculation over a series of digitalized virtual proving ground road profiles.

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.

Powertrain electrification is becoming increasingly common in the transportation sector to address the challenges of global warming and deteriorating air quality. This paper introduces a novel “Build Your Hybrid” approach to experience and test various hybrid powertrain concepts. This approach is applied to the light commercial vehicles (LCV) segment due to the attractive combination of a Diesel engine and a partly electrified powertrain. For this purpose, a demonstrator vehicle has been set up with a flexible P02 hybrid topology and a prototype Hybrid Control Unit (HCU). Based on user input, the HCU software modifies the control functions and simulation models to emulate different sub-topologies and levels of hybridization in the demonstrator vehicle. Three powertrain concepts are considered for LCVs: HV P2, 48V P2 and 48V P0 hybrid. Dedicated hybrid control strategies are developed to take full advantage of the synergies of the electrical system and reduce CO2 and NOx emissions.

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.

ISO/SAE 21434 [1] Final International Standard was released September 2021 to great fanfare and is the most prominent standard in Automotive Cybersecurity. As members of the Joint Working Group (JWG) the authors spent 5 years developing the 84 pages of precise wording acceptable to hundreds of contributors. At the same time the auto industry had been undergoing a metamorphosis probably unmatched in its hundred-year history. A centerpiece of the metamorphosis is the adoption of the Agile development method to meet market demands for time-to-market and flexibility of design. Unfortunately, a strategic decision was made by the JWG to focus ISO/SAE 21434 on the V-Model method. Agile does not break ISO/SAE 21434. Agile is a framework that can be adapted to suit any process. In the end the goals are the same regardless of development method; security by design must be achieved.

The reduction of harmful emissions is a key challenge in fighting climate change and global warming. Besides battery electric vehicles (BEVs), improved engine efficiency and alternate fuels, such as e-fuels or biofuels, can improve the emission budget of the transportation sector. Pred ictive simulations can be utilized as these avoid relying on slow manufacturing processes and expensive experiments. As the properties of alternative fuels can change drastically compared to classical fuels, even engine parameters, such as the mass flow rate, need to be reevaluated and optimized. However, simulation frameworks often rely on mass flow rates as input quantity, and hence, a prediction is impossible. This paper gives accurate pressure-based boundary conditions for multiphase systems and focuses on equations of state (EOS) employed in homogeneous equilibrium models (HEMs). Additionally, a dual-density approach is introduced to correct modeling errors that are intrinsic to a particular EOS.

A large amount of heat is generated in electric vehicle battery packs during high rate charging, resulting in the need for effective cooling methods. In this paper, a prototype liquid cooled large format Lithium-ion battery module is modeled and tested. Experiments are conducted on the module, which includes 31Ah NMC/Graphite pouch battery cells sandwiched by a foam thermal pad and heat sinks on both sides. The module is instrumented with twenty T-type thermocouples to measure thermal characteristics including the cell and foam surface temperature, heat flux distribution, and the heat generation from batteries under up to 5C rate ultra-fast charging. Constant power loss tests are also performed in which battery loss can be directly measured.