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The paper solves the problem of increasing the accuracy of measuring torque and use of an electronic torque meter as a feedback sensor of synchronous and induction machines of an electric traction drive. Relevance of the problem and methods for its solving by indirect means using simulation models of electric machines are considered. The theoretical development of the meter is based on the energy model of electric machines in the form of differential equations for active and reactive power balance. This eliminates the direct influence of instability and nonlinearity of inductive elements and takes into account electrical, magnetic, mechanical, and harmonic losses using the simplest algorithms. Key variables of the model in the form of total active power and angular velocity are measured directly, and the high nominal efficiency of traction machines (95%) provides a wide tolerance range for calculating total losses.

With the rapid development of electric vehicles, the demands for lithium-ion batteries and advanced battery technologies are growing. Today, lithium-ion batteries mainly use liquid electrolytes, containing organic compounds such as dimethyl carbonate and ethylene carbonate as solvents for the lithium salts. However, when thermal runaway occurs, the electrolyte decomposes, venting combustible gases that could readily be ignited when mixed with air and leading to pronounced heat release from the combustion of the mixture. So far, the chemical behavior of electrolytes during thermal runaway in lithium-ion batteries is not comprehensively understood. Well-validated compact chemical kinetic mechanisms of the electrolyte components are required to describe this process in CFD simulations. In this work, submechanisms of dimethyl carbonate and ethylene carbonate were developed and adopted in the Ansys Model Fuel Library (MFL).

Carbon-neutral (CN) fuels will be part of the solution to reducing global warming effects of the transportation sector, along with electrification. CN fuels such as hydrogen, ammonia, biofuels, and e-fuels can play a primary role in some segments (aviation, shipping, heavy-duty road vehicles) and a secondary role in others (light-duty road vehicles). The composition and properties of these fuels vary substantially from existing fossil fuels. Fuel effects on performance and emissions are complex, especially when these fuels are blended with fossil fuels. Predictively modeling the combustion of these fuels in engine and combustor CFD simulations requires accurate representation of the fuel blends. We discuss a methodology for matching the targeted fuel properties of specific CN fuels, using a blend of surrogate fuel components, to form a fuel model that can accurately capture fuel effects in an engine simulation.

In-flight icing significantly influences the design of large passenger aircraft. Relevant aspects include sizing of the main aerodynamic surfaces, provision of anti-icing systems, and setting of operational restrictions. Empennages of large passenger aircraft are particularly affected due to the small leading edge radius, and the requirement to generate considerable lift for round out and flare, following an extended period of descent often in icing conditions. This paper describes a CFD-based investigation of the effects of sweep on the aerodynamic performance of a novel forward-swept horizontal stabilizer concept in icing conditions. The concept features an unconventional forward sweep, combined with a high lift leading edge extension (LEX) located within a fuselage induced droplet shadow zone, providing passive protection from icing.

This paper introduces the Lagrangian particle tracking technology readily available in Ansys Fluent in the in-flight icing simulation workflow, which normally uses the Eulerian approach for droplet flows. The Lagrangian solver is incorporated in the Fluent Icing workspace which is to become the next-gen in-flight icing simulation tool provided by Ansys. Lagrangian tracking will eventually be used for SLD and ice crystal rebound and re-impingement calculations in the Ansys workflow. Here we introduce some preliminary results with the current state of its implementation as of Fluent Icing release 2023R2. Example cases include several selections from the 1st Ice prediction workshop with experimental comparisons as well as results obtained earlier with the Eulerian droplet solution strategy. Collection efficiency comparisons on clean geometries show good agreement between Eulerian and Lagrangian methods when the particle seeds are in the millions range.

This paper presents the current state of a three-layer surface icing model for ice crystal icing risk assessment in aircraft engines, being developed jointly by Ansys and Honeywell to account for possible heat transfer from inside an engine into the flow path where ice accretion occurs. The bottom layer of the proposed model represents a thin metal sheet as a substrate surface to conductively transfer heat from an engine-internal reservoir to the ice layer. The middle layer is accretion ice with a porous structure able to hold a certain amount of liquid water. A shallow water film layer on the top receives impinged ice crystals. A mass and energy balance calculation for the film determines ice accretion rate. Water wicking and recovery is introduced to transfer liquid water between film layer and porous ice accretion layer.

This paper studies the level of confidence and applicability of CFD simulations using steady-state Reynolds-Averaged Navier-Stokes (RANS) in predicting aerodynamic performance losses on swept-wings due to contamination with ice accreted in-flight. The wing geometry selected for the study is the 65%-scale Common Research Model (CRM65) main wing, for which NASA Glenn Research Center’s Icing Research Tunnel has generated experimental ice shapes for the inboard, mid-span, and outboard sections. The reproductions at various levels of fidelity from detailed 3D scans of these ice shapes have been used in recent aerodynamic testing at the Office National d’Etudes et Recherches Aérospatiales (ONERA) and Wichita State University (WSU) wind tunnels. The ONERA tests were at higher Reynolds number range in the order of 10 million, while the WSU tests were in the order of 1 million.

Owing to their weight saving potential and improved flexural stiffness, metal-polymer-metal sandwich laminates are finding increasing applications in recent years. Increased use of such laminates for automotive body panels and structures requires not only a better understanding of their mechanical behavior, but also their formability characteristics. This study focuses on the formability of a metal–polymer-metal sandwich laminate that consists of AA5182 aluminum alloy as the outer skin layers and polypropylene (PP) as the inner core. The forming limit curves of Al/PP/Al sandwich laminates are determined using finite element simulations of Nakazima test specimens. The numerical model is validated by comparing the simulated results with published experimental results. Strain paths for different specimen widths are recorded.

The safety, performance, and operational life of power dense Lithium-ion batteries used in Hybrid and Electric Vehicles are dependent on the operating temperature. Modeling and simulation are essential tools used to accelerate the design process of optimal thermal management systems. However, high-fidelity 3D computational fluid dynamics (CFD) simulation of such systems is often difficult and computationally expensive. In this paper, we demonstrate a multi-part coupled system model for simulating the heating/cooling system of the traction battery at a module level. We have reduced computational time by employing reduced-order modeling (ROM) framework on separate 3D CFD models of the battery module and the cooling plate. The order of the thermal ROM has also been varied to study the trade-off between accuracy, fidelity, and complexity. The ROMs are bidirectionally coupled to an empirical battery model built from in-house test data.

A driver model in multibody dynamic analysis software is to run a vehicle dynamics model in various customer applications: handling events such as lane changes and circle turns, and durability events such as Belgian blocks, hill courses, driveways, and race tracks. Ansys Motion is a robust multibody dynamic analysis software for many applications including vehicle dynamics simulations. This paper discusses Ansys Driver development in Ansys Motion. It addresses developments of critical driver features: identification of vehicle handling capability, a path planning from complex road profiles, an analog filter design, and a longitudinal and lateral control of vehicle models. It also discusses how to achieve the robustness of the driver model for various customer simulation scenarios not affecting simulation output due to too much driver control. This study presents a couple of examples of handling and durability event simulations.

Controller Area Network (CAN), the de facto standard for in-vehicle networks, has insufficient security features and thus is inherently vulnerable to various attacks. To protect CAN bus from attacks, intrusion detection systems (IDSs) based on advanced deep learning methods, such as Convolutional Neural Network (CNN) and Recurrent Neural Network (RNN), have been proposed to detect intrusions. However, those models generally introduce high latency, require considerable memory space, and often result in high energy consumption. To accelerate intrusion detection and also reduce memory requests, we exploit the use of Binarized Neural Network (BNN) and hardware-based acceleration for intrusion detection in in-vehicle networks. As BNN uses binary values for activations and weights rather than full precision values, it usually results in faster computation, smaller memory cost, and lower energy consumption than full precision models.

Tubular sections are found in many automotive structural components such as front rails, cross beams, and sub-frames. They are also used in other vehicular structures, such as buses and rails. In many of these components, smaller tubular sections may be joined together using an adhesive to build the required structure. For crash safety applications, it is important that the joined tube sections be able to provide high energy absorption capability and withstand the impact load before the adhesive bond failure occurs. In this study, single lap tubular joints between two aluminum tubes are investigated for their crush performance at both quasi-static and high impact speeds using finite element analysis. A crash optimized adhesive Betamate 1496 is considered. The joint parameters, such as adhesive overlap length, tube diameters and tube lengths, are varied to determine their effects on energy absorption, peak and mean loads, and tube deformation mode.

With the emphasis of electrification in automotive industry, tremendous efforts are made to develop electric motors with high efficiency and power density, and reduce noise, vibration and harshness (NVH). A multiphysics simulation workflow is used to predict the eccentricity-induced noise for GM’s Bolt EV motor. Both static and dynamic eccentricities are investigated along with axial tilt. Analysis results show that these eccentricities play a critical role in the NVH behavior of the motor assembly. Transient electromagnetic (EM) analysis is performed first by extruding 2D stator and rotor sections to form 3D EM models. Sector model is duplicated to form full 360-degree model. Stator is split into three rotated sections to characterize stator skew, and the skew between two sections of rotor and magnets are also modelled. Sinusoidal current is applied and lumped-sum forces on each stator tooth are computed.

Semi-trucks, specifically class-8 trucks, have recently become a platform of interest for autonomy systems. Platooning involves multiple trucks following each other in close proximity, with only the lead truck being manually driven and the rest being controlled autonomously. This approach to semi-truck autonomy is easily integrated on existing platforms, reduces delivery times, and reduces greenhouse gas emissions via fuel economy benefits. Level 1 SAE fuel studies were performed on class-8 trucks operating with the Auburn Cooperative Adaptive Cruise Control (CACC) system, and fuel savings up to 10-12% were seen. Enabling platooning autonomy required the use of radar, global positioning systems (GPS), and wireless vehicle-to-vehicle (V2V) communication. Poor measurements and state estimates can lead to incorrect or missing positioning data, which can lead to unnecessary dynamics and finally wasted fuel.

Autonomy for multiple trucks to drive in a fixed-headway platoon formation is achieved by adding precision GPS and V2V communications to a conventional adaptive cruise control (ACC) system. The performance of the Cooperative ACC (CACC) system depends heavily on the reliability of the underlying V2V communications network. Using data recorded on precision-instrumented trucks at both ACM and NCAT test tracks, we provide an understanding of various effects on V2V network performance: Occlusions - non-line-of-sight (NLOS) between the Tx and Rx antenna may cause network signal loss. Rain - water droplets in the air may cause network signal degradation. Antenna position - antennas at higher elevation may have less ground clutter to deal with. RF interference - interference may cause network packet loss. GPS outage - outages caused by tree cover, tunnels, etc. may result in degraded performance. Road curvature - curves may affect antenna diversity.

In frontal collision of vehicles, the front bumper system is the first structural member that receives the energy of collision. In low speed impacts, the bumper beam and the crush cans that support the bumper beam are designed to protect the engine and the radiator from being damaged, while at high speed impacts, they are required to transfer the energy of impact as uniformly as possible to the front rails that contributes to the occupant protection. The bumper beam material today is mostly steels and aluminum alloys, but carbon fiber composites have the potential to reduce the bumper weight significantly. In this study, crash performance of bumper beams made of a boron steel, aluminum alloy 5182 and a carbon fiber composite with steel crush cans is examined for their maximum deflection, load transfer to crush cans, total energy absorption and failure modes using finite element analysis.

Accurate modeling of the characteristics of diesel-engine combustion leads to more efficient design. Accurate modeling in turn depends on correctly capturing spray dynamics, turbulence, and fuel chemistry. This work presents a computational fluid dynamics (CFD) investigation of a well characterized small-bore direct injection diesel engine at Sandia National Laboratories’ Combustion Research Facility. The engine has been studied for two piston-bowls geometries and various injection timings. Simulation of these conditions test the predictive capabilities of our approach to diesel engine modeling using Ansys Forte. An experimental database covering a wide range of operating conditions is provided by the Engine Combustion Network for this engine, which is used to validate our modeling approach. Automatic and solution-adaptive meshing is used, and the recommended settings are discussed.

The new wireless rotor electrical machine has all the coils placed on the stator. The laminated wireless rotor serves as a magnetic field switcher. A wireless rotor is cold, and it facilitates machine cooling. The model of the wireless rotor machine includes electrical and mechanical components. The wireless rotor machines can find an application in practice because they have advantages over existing devices. In modeling, we use a new approach. We consider a motor as a natural control system with torque feedback. Such an approach simplifies analyses and adjustment of the operation of an electrical machine. First, we analyze an open-loop control system without torque feedback. In this case, by changing the rotor speed under external torque, we can receive the torque-speed motor characteristics. After some adjustments to the open-loop system, we can consider the close loop control system with torque feedback. We use a space vector representation for sinusoidal electric components.

Accurately predicting the evolution of soot mass and soot particle numbers under engine conditions is critical to advanced engine design. A detailed soot-chemistry model that can capture soot under gasoline and diesel conditions without tuning is necessary for such predictions. Building confidence in the predictive usage of the chemistry in engine simulations requires validating the soot kinetics over a wide range of operating conditions and fuels, using data from different experimental techniques, and using sources from laboratory flames to engines. This validation study focuses on a soot-chemistry model that considers multiple nucleation, growth, and oxidation reaction pathways. It involves 14 gas-phase precursors and considers the effect of different soot-particle surface sites.

The engine operating point (EOP), which is determined by the engine speed and torque, is an important part of a vehicle's powertrain performance and it impacts FC, available propulsion power, and emissions. Predicting instantaneous EOP in real-time subject to dynamic driver behaviour and environmental conditions is a challenging problem, and in existing literature, engine performance is predicted based on internal powertrain parameters. However, a driver cannot directly influence these internal parameters in real-time and can only accommodate changes in driving behaviour and cabin temperature. It would be beneficial to develop a direct relationship between the vehicle-level parameters that a driver could influence in real-time, and the instantaneous EOP. Such a relationship can be exploited to dynamically optimize engine performance.