Search Results

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.

The study focuses on understanding the air and oil flow characteristics within a ball bearing during high-speed rotation, with a particular emphasis on optimizing frictional heat dissipation and oil lubrication methods. Computational fluid dynamics (CFD) techniques are employed to analyze the intricate three-dimensional airflow and oil flow patterns induced by the motion of rotating and orbiting balls within the bearing. A significant challenge in conducting three-dimensional CFD studies lies in effectively resolving the extremely thin gaps existing between the balls, races, and cages within the bearing assembly. In this research, we adopt the ball-bearing structured meshing strategy offered by Simerics-MP+ to meticulously address these micron-level clearances, while also accommodating the rolling and rotation of individual balls. Furthermore, we investigate the impact of different designs of the lubrication ports to channel oil to other locations compared to the ball bearings.

Effective design of the lubrication path greatly influences the durability of any transmission system. However, it is experimentally impossible to estimate the internal distribution of the automotive transmission fluid (ATF) to different parts of the transmission system due to its structural complexities. Hybrid vehicle transmission systems usually consist of different types of bearings (ball bearings, thrust bearings, roller bearings, etc.) in conjunction with gear systems. It is a perennial challenge to computationally simulate such complicated rotating systems. Hence, one-dimensional models have been the state of the art for designing these intricate transmission systems. Though quantifiable, the 1D models still rely heavily on some testing data. Furthermore, HEVs (hybrid electric vehicles) desire a more efficient lubrication system compared to their counterparts (Internal combustion engine vehicles) to extend the range of operation on a single charge.

Performance testing and evaluation always plays an important role in the developmental process of a vehicle, which also applies to autonomous vehicles. The complex nature of an autonomous vehicle from architecture to functionality demands even more quality-and-quantity controlled testing and evaluation than ever before. Most of the existing testing methodologies are task-or-scenario based and can only support single or partial functional testing. These approaches may be helpful at the initial stage of autonomous vehicle development. However, as the integrated autonomous system gets mature, these approaches fall short of supporting comprehensive performance evaluation. This paper proposes a novel hierarchical and systematic testing and evaluation approach to bridge the above-mentioned gap.

This paper presents a method for optimization design of an engine mounting system subjected to some constraints. The engine center of gravity, the mount stiffness rates, the mount locations and/or their orientations with respect to the vehicle can be chosen as design variables, but some of them are given in advance or have limitations because of the packaging constraints on the mount locations, as well as the individual mount rate ratio limitations imposed by manufacturability. A computer program, called DynaMount, has been developed that identifies the optimum design variables for the engine mounting system, including decoupling mode, natural frequency placement, etc.. The degree of decoupling achieved is quantified by kinetic energy distributions calculated for each of the modes. Several application examples are presented to illustrate the validity of this method and the computer program.

Once the design of a door sheetmetal and accessories is confirmed, the acoustics of the door system depends on the sound package assembly. This essentially consists of a watershield which acts as a barrier and a porous material which acts as an absorber. The acoustical performance of the watershield and the reverberant sound build-up in the door cavity control the performance. This paper discusses the findings of a design study that was developed based on design of experiments (DOE) concepts to determine which parameters of the door sound package assembly are important to the door acoustics. The study was based on conducting a minimum number of tests on a five factor - two level design that covered over 16 different design configurations. In addition, other measurements were made that aided in developing a SEA model which is also compared with the findings of the results of the design study.

During a vehicle drive cycle, the oil in the engine oil pan sloshes very vigorously due to the acceleration of the vehicle. This can cause the pickup tube in the engine oil pan to become uncovered from oil and exposed to air, which affects the lubrication pump performance. Engine oil pan sloshing is inherently a 3D problem as the free oil surface is constantly changing. Multi-dimensional Computational Fluid Dynamics (CFD) methods are very useful to simulate such problems with high detail and accuracy but are computationally very expensive. Part of the engine lubrication system, such as the pump, can be modelled in 1D which can predict accurate results at relatively high computational speeds. By utilizing the advantages of both 1D and 3D CFD models, a coupled 1D-3D simulation approach has been developed to capture the detailed oil sloshing phenomenon in SimericsMP+ and the system level simulation is conducted in GT-SUITE where 3D spatial data is not required.

A continuously variable lift, duration and phase mechanical lift mechanism is described, as applied to the intake valvetrain of a SOHC, 4-valve per cylinder, four-cylinder production engine. Improvements in fuel economy were sought by reduction of pumping losses and improved charge preparation, and optimization of WOT torque was attempted by variation of intake valve closing angle. Adjustment of the mechanism is achieved by movement of the pivot shaft for the rocker arms. The relationship between lift, duration and phase is predetermined at the design stage, and is fixed during operation. There is considerable design flexibility to achieve the envelope of lift curves deemed desirable. The operation of the mechanism is described, as are the development procedure, testing with fixed cams, some cycle simulation, friction testing on a separate rig and dyno testing results for idle, part load and WOT.

Fault diagnosis for automotive systems is driven by government regulations, vehicle repairability, and customer satisfaction. Several methods have been developed to detect and isolate faults in automotive systems, subsystems and components with special emphasis on those faults that affect the exhaust gas emission levels. Limit checks, model-based, and knowledge-based methods are applied for diagnosing malfunctions in emission control systems. Incipient and partial faults may be hard to detect when using a detection scheme that implements any of the previously mentioned methods individually; the integration of model-based and knowledge-based diagnostic methods may provide a more robust approach. In the present paper, use is made of fuzzy residual evaluation and of a fuzzy expert system to improve the performance of a fault detection method based on a mathematical model of the engine.

Laser lap welding quality is a non-linear response based on a host of categorical and numeric material and process variables. This paper describes a Grammatical Evolution approach to the structure identification of the laser lap welding process and compares its performance with linear regression and a neuro-fuzzy inference system.

As vehicle development timelines continue to shorten, it is necessary for the full vehicle NVH engineer to be able to predict performance without actual prototypes. There has been significant advancement in the accuracy of finite element modeling techniques of trimmed bodies; however accuracy is still low in the road noise mid frequency range from 150-400Hz. Also, calculation times for these frequencies are long, with very large results files in some cases. To alleviate these limitations, a Hybrid approach has been used, where a finite element suspension and drive train model is coupled with a test based Frequency Response Function (FRF) model of the trimmed body. The predicted road noise level was compared to actual vehicle tests and exhibited excellent correlation.

High temperature components in internal combustion engines and exhaust systems must withstand severe mechanical and thermal cyclic loads throughout their lifetime. The combination of thermal transients and mechanical load cycling results in a complex evolution of damage, leading to thermomechanical fatigue (TMF) of the material. Analytical tools are increasingly employed by designers and engineers for component durability assessment well before any hardware testing. The DTMF model for TMF life prediction, which assumes that micro-crack growth is the dominant damage mechanism, is capable of providing reliable predictions for a wide range of high-temperature components and materials in internal combustion engines. Thus far, the DTMF model has employed a local approach where surface stresses, strains, and temperatures are used to compute damage for estimating the number of cycles for a small initial defect or micro-crack to reach a critical length.

In a gasoline engine, the unswept in-cylinder residual gas and introduction of external EGR is one of the important means of controlling engine raw NOx emissions and improving part load fuel economy via reduction of pumping losses. Since the trapped in-cylinder Residual Gas Fraction (RGF, comprised of both internal, and external) significantly affects the combustion process, on-line diagnosis and monitoring of in-cylinder RGF is very important to the understanding of the in-cylinder dilution condition. This is critical during the combustion system development testing and calibration processes. However, on-line measurement of in-cylinder RGF is difficult and requires an expensive exhaust gas analyzer, making it impractical for every application. Other existing methods, based on measured intake and exhaust pressures (steady state or dynamic traces) to calculate gas mass flowrate across the cylinder ports, provide a fast and economical solution to this problem.

To accurately evaluate the energy consumption benefits provided by connected and automated vehicles (CAV), it is necessary to establish a reasonable baseline virtual driver, against which the improvements are quantified before field testing. Virtual driver models have been developed that mimic the real-world driver, predicting a longitudinal vehicle speed profile based on the route information and the presence of a lead vehicle. The Intelligent Driver Model (IDM) is a well-known virtual driver model which is also used in the microscopic traffic simulator, SUMO. The Enhanced Driver Model (EDM) has emerged as a notable improvement of the IDM. The EDM has been shown to accurately forecast the driver response of a passenger vehicle to urban and highway driving conditions, including the special case of approaching a signalized intersection with varying signal phases and timing. However, most of the efforts in the literature to calibrate driver models have focused on passenger vehicles.

This paper examines the conformability of elastic piston rings to a distorted cylinder bore. Several bounds are available in the literature to help estimate the maximum allowable Fourier coefficient in a Fourier expansion of bore distortion: the analytically derived bounds in [7] and [8], and the semi-empirically derived bounds discussed in [9]. The underlying assumptions for each set of analytic bounds are examined and a multiple order algorithm is derived. The proposed algorithm takes account of multiple orders of distortion at once. It is tested with finite element (FE) data and compared to the classical bound approach. The results indicate that the bounds in [7] are compatible with linear elasticity theory (LET), whereas the bounds in [8] are not. Furthermore, numerical evidence indicates that the present multiple order algorithm can predict seal breaches more accurately than either of the other analytic bounds.

Rotating clutches play an important role in automatic transmissions (AT), dual-clutch transmissions (DCT) and hybrid transmissions. It is very important to continually improve the transmission systems in the areas such as simplifying actuator designs, reducing cost and increasing controllability. A new concept of electrical motor driven actuation using a wedge mechanism, a wedge clutch, demonstrates potential benefits. This wedge clutch has the characteristics of good mechanical advantage, self-reinforcement, and faster and more precise controllability using electrical motor. In this paper, a new rotating wedge clutch is proposed. It presents a challenge since the motor actuator has to be stationary while the clutch piston is rotating. A new mechanism to connect the motor to the wedge piston, including dual-plane bearings and two mechanical ramp linkages, is studied. The design and verification of the physical structure of the actuator are discussed in detail in the paper.

With the increasing emphasis on Systems Engineering, there is a need to ensure that Electrical/Electronic (E/E) Systems Endurance Testing of vehicles, in a real world environment, prior to Production Launch, is performed in a manner and at a technological level that is commensurate with the high level of electronics and computers in contemporary vehicles. Additionally, validating the design and performance of individual standalone electronic systems and modules “on the bench” does not guarantee that all the permutations and combinations of real-world hardware, software, and driving conditions are taken into account. Traditional Proving Ground (PG) vehicle testing focuses mainly on powertrain durability testing, with only a simple checklist being used by the PG drivers as a reminder to cycle some of the electrical components such as the power window switches, turn signals, etc.

Knowledge of the tire slip ratio can greatly improve vehicle longitudinal stability and its dynamic performance. Most conventional slip ratio observers were mainly designed based on input of non-driven wheel speed and estimated vehicle speed. However, they are not applicable for electric vehicles (EVs) with four in-wheel motors. Also conventional methods on speed estimation via integration of accelerometer signals can often lead to large offset by long-time integral calculation. Further, model uncertainties, including steady state error and unmodeled dynamics, are considered as additive disturbances, and may affect the stability of the system with estimated state error. This paper proposes a novel slip ratio observer based on input-to-state stability (ISS) method for electric vehicles with four-wheel independent driving motors.

Over the last decade, many methods have been proposed for estimating the in-cylinder combustion pressure or the torque from instantaneous crankshaft speed measurements. However, such approaches are typically computationally expensive. In this paper, an entirely different approach is presented to allow the real-time estimation of the in-cylinder pressures based on crankshaft speed measurements. The technical implementation of the method will be presented, as well as extensive results obtained for a V-6 S.I. engine while varying spark timing, engine speed, engine load and EGR. The method allows to estimate the in-cylinder pressure with an average estimation error of the order of 1 to 2% of the peak pressure. It is very general in its formulation, is statistically robust in the presence of noise, and computationally inexpensive.

The design and development of electric vehicles involves many unique challenges. One such challenge involves accurately predicting driveline abuse torque loads early in the design cycle to aid with sizing drive-unit and driveline components. Since electrified drivelines typically lack a torque-limiting “fuse” element such as a torque converter or slipping clutch, they can be vulnerable to sudden transient events involving high wheel acceleration or deceleration. Component sizing must account for the loads caused by such events, and these loads must be accurately quantified early on when vehicle parameters haven’t been finalized yet. Early load predictions can be made by completing abuse maneuver simulations where key parameters are varied to gauge their influence on simulated loads. Understanding how these parameters impact loads allows for better risk assessment during the design process, as these parameters will inevitably change until a final design is iterated upon.