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Electrified powertrains will play a growing role in meeting global fuel consumption and CO2 requirements. In support of this, FCA US has developed its first dedicated hybrid transmission (the eFlite® transmission), used in the Chrysler Pacifica Hybrid. The Chrysler Pacifica is the industry’s first electrified minivan. [2] The new eFlite hybrid transmission architecture optimizes performance, fuel economy, mass, packaging and NVH. The transmission is an electrically variable FWD transaxle with an input split configuration and incorporates two electric motors, both capable of driving in EV mode. The lubrication and cooling system makes use of two pumps, one electrically operated and one mechanically driven. The Chrysler Pacifica has a 16kWh lithium ion battery and a 3.6-liter Pentastar® engine which offers total system power of 260 hp with 84 MPGe, 33 miles of all electric range and 566 miles total driving range. [2] This paper’s focus is on the eFlite transmission.

Improvement of vehicle path-tracking performance not only affects the vehicle driving safety and comfort but is also essential for autonomous driving technology. The current research focuses on vehicle path-tracking control study and application of dual-motor SBW system. The preview driver model is developed by considering the lateral and yaw tracking. MPC (model predictive control) and LQR (linear quadratic regulator) path following controllers are developed to compare the tracking control performance. A steer-by-wire (SBW) system of dual-motor configuration is designed with permanent magnet synchronous motor (PMSM) control scheme. Finally, the proposed control methods are verified with different driving cases, which shows that the system can effectively achieve small tracking errors in the simulation, and also can be applied in the future autonomous driving or advanced driver assistance system to maintain the lateral and yaw errors within a safe range during path-tracking.

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.

The advanced Optimization techniques help us in exploring the light weight architecture. This paper explains the process of designing a lightweight track bar bracket, which satisfies all durability performance targets. The mounting locations and load paths are critical factors that define the performance and help in the development of weight efficient structure. The process is to identify the appropriate bolt location through Design of Experiment (DOE) and topology based studies; followed by section and shape optimization that help to distribute material in a weight efficient manner across the structure. Load path study using topology optimization is performed to identify the load path for durability load cases. Further shape optimization is done using hyper study to determine the exact thickness of the webs and ribs. A significant weight reduction from the baseline structure is observed. This process may be applicable for all casting components.

The key hurdles to achieving wide consumer acceptance of battery electric vehicles (BEVs) are weather-dependent drive range, higher cost, and limited battery life. These translate into a strong need to reduce a significant energy drain and resulting drive range loss due to auxiliary electrical loads the predominant of which is the cabin thermal management load. Studies have shown that thermal sub-system loads can reduce the drive range by as much as 45% under ambient temperatures below −10 °C. Often, cabin heating relies purely on positive temperature coefficient (PTC) resistive heating, contributing to a significant range loss. Reducing this range loss may improve consumer acceptance of BEVs. The authors present a unified thermal management system (UTEMPRA) that satisfies diverse thermal and design needs of the auxiliary loads in BEVs.

This paper introduces a novel approach to modeling Torque Converter (TC) in conventional and hybrid vehicles, aiming to enhance torque delivery accuracy and efficiency. Traditionally, the TC is modelled by estimating impeller and turbine torque using the classical Kotwicki’s set of equations for torque multiplication and coupling regions or a generic lookup table based on dynamometer (dyno) data in an electronic control unit (ECU) which can be calibration intensive, and it is susceptible to inaccurate estimations of impeller and turbine torque due to engine torque accuracy, transmission oil temperature, hardware variation, etc. In our proposed method, we leverage an understanding of the TC inertia – torque dynamics and the knowledge of the polynomial relationship between slip speed and fluid path torque. We establish a mathematical model to represent the polynomial relationship between turbine torque and slip speed.

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.

Material formability is a very important aspect in the automotive stamping, which must be tested for the success of manufacturing. One of the most important sheet metal formability parameters for the stamping is the edge tear-ability. In this paper, a novel test method has been present to test the aluminum sheet edge tear-ability with 3D digital image correlation (DIC) system. The newly developed test specimen and fixture design are also presented. In order to capture the edge deformation and strain, sample's edge surface has been sprayed with artificial speckle. A standard MTS tensile machine was used to record the tearing load and displacement. Through the data processing and evaluation of sequence image, testing results are found valid and reliable. The results show that the 3D DIC system with double CCD can effectively carry out sheet edge tear deformation. The edge tearing test method is found to be a simple, reliable, high precision, and able to provide useful results.

Draw beads are widely used in the binder of a draw die for regulating the restraining force and control the draw-in of a metal blank. Different sheet materials and local panel geometry request different local draw bead configurations. Even the majority of draw bead is single draw bead, the alternative double draw bead does have its advantages, such as less bending damage may be brought to the sheet material and more bead geometry features available to work on. In this paper, to measure the pulling force when a piece of sheet metal passing through a draw bead on an inclined binder, the AA5XXX and AA6XXX materials were tested and its strain were measured with a digital image correlation (DIC) system. Five different types of double bead configurations were tested. The beads are installed in a Stretch-Bend-Draw-System (SBDS) test device. The clearance between a male and a female bead is 10% thicker than the sheet material. A tensile machine was used to record the pulling force.

Light-weighting vehicles cause an increase in Aluminum Alloy stamping processes in the Automotive Industry. Surface finish and lubricants of aluminum alloy (AA) sheet play an important role in the deep drawing processes as they can affect the friction condition between the die and the sheet. This paper aims to develop a reliable and practical laboratory test method to experimentally investigate the influence of surface finish, lubricant conditions, draw-bead clearances and pulling speed on the frictional sliding behavior of AA 6XXX sheet metal. A new double-beads draw-bead-simulator (DBS) system was used to conduct the simulated test to determine the frictional behavior of an aluminium alloy with three surface lubricant conditions: mill finish (MF) with oil lube, electric discharge texture (EDT) finish with oil lube and mill finish (MF) with dry lube (DL).

Bendability is one of the most important formability characteristics in sheet metal forming, so it has to be understood for robust aluminum stamping process designs. Crack is one of the major failure modes in aluminum sheet bending. In this study, a new “incremental bending” method is proposed to reduce the risk of bending failure. A novel laboratory test methodology is conducted to test the 5xxx series aluminum sheet bendability with 3D digital image correlation (DIC) measurement system. The designs of test apparatus and test procedure are introduced in this paper. Through the data processing and evaluation of a sequence image acquisition, the major strain histories within the zone of the through thickness crack of test samples are measured. Testing results show that incremental bending is capable of reducing peak strain on the outer surface obviously compared with traditional non-incremental bending. The more step, more movement, the more peak strain reduction.

This research studies the transformation kinetics of austempered ductile iron (ADI) with and without nickel as the main alloying element. ADI has improved mechanical properties compared to ductile iron due to its ausferrite microstructure. Not only can austempered ductile iron be produced with high strength, high toughness and high wear resistance, the ductility of ADI can also be increased due to high carbon content austenite. Many factors influence the transformation of phases in ADI. In the present work, the addition of nickel was investigated based on transformation kinetics and metallography observation. The transformation fractions were determined by Rockwell hardness variations of ADI specimens. The calculation of transformation kinetics and activation energy using the “Avrami Equation” and “Arrhenius Equation” is done to describe effects of nickel alloy for phase reactions.

Battery state-of-charge (SOC) is critical information for the vehicle energy management system and must be accurately estimated to ensure reliable and affordable electrified vehicles (xEV). However, due to the nonlinear temperature, health, and SOC dependent behaviour of Li-ion batteries, SOC estimation is still a significant automotive engineering challenge. Traditional approaches to this problem, such as electrochemical models, usually require precise parameters and knowledge from the battery composition as well as its physical response. In contrast, neural networks are a data-driven approach that requires minimal knowledge of the battery or its nonlinear behaviour. The objective of this work is to present the design process of an SOC estimator using a deep feedforward neural network (FNN) approach. The method includes a description of data acquisition, data preparation, development of an FNN, FNN tuning, and robust validation of the FNN to sensor noise.

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.

Damages (fracture) in metals are caused by material degradation due to crack initiation and growth due to fatigue or dynamic loadings. The accurate and realistic modeling of an inelastic behavior of metals is essential for the solution of various problems occurring in engineering fields. Currently, various theories and failure models are available to predict the damage initiation and the growth in metals. In this paper, the failure of aluminum alloy is studied using progressive damage and failure material model using Abaqus explicit solver. This material model has the capability to predict the damage initiation due to the ductile and shear failure. After damage initiation, the material stiffness is degraded progressively according to the specified damage evolution response. The progressive damage models allow a smooth degradation of the material stiffness, in both quasi-static and dynamic situations.

Euro NCAP Pedestrian head impact protocol mandates the reduction of head injuries, measured using head injury criteria (HIC). Virtual tools driven design comprises of simulating the impact on the hood and post processing the results. Due to the high number of impact points, engineers spend a significant portion of their time in manual data management, processing, visualization and score calculation. Moreover, due to large volume of data transfer from these simulations, engineers face data bandwidth issues particularly when the data is in different geographical locations. This deters the focus of the engineer from engineering and also delays the product development process. This paper describes the development of an automated method using d3VIEW that significantly improves the efficiency and eliminates the data volume difficulties there by reducing the product development time while providing a higher level of simulation results visualization.

Modern Instrument Panel Clusters (IPC) are equipped with thin film transistor (TFT) based displays. Contrary to conventional IPCs with hard gauges and liquid crystal diode (LCD) displays, TFT displays offer versatile usage of display area with soft gauges, reconfigurable menus, tell tales, graphics and warning messages etc., At the same time, the number of possible screen combinations, multicolor images validation and different screen arbitration become significantly complex. Thereby display validation turns out to be a complex and time consuming task in IPC validation. The task becomes even more complex when change requests are to be incorporated during final phases of development stage. This paper provides a novel solution that helps to validate any graphical and behavioral changes with minimum effort and maximum accuracy.

This paper proposes an optimization-based transmission gear shifting strategy for electrified powertrains with a transmission. With the demand for reduced vehicle emissions, electrified propulsion systems have garnered significant attention due to their potential to improve vehicle efficiency and performance. An electrified propulsion system architecture of significance includes multiple electric motors and a transmission where some driveline actuators can transmit torque through changing gear ratios. If there is at least one electric motor arranged before the input of the transmission and at least one after the transmission output, a unique design opportunity arises to shift gears in the most energy efficient manner.

One of the advantages of hybrid vehicles is the ability to operate the engine more optimally at a low brake specific fuel consumption (BSFC) as compared to conventional vehicles. This ability of hybrid vehicles is a major factor contributing to the fuel economy improvement over conventional vehicles. Unlike conventional gasoline powertrains, hybrid powertrains allow engine to be switched off and use battery power to propel vehicles. In order to maintain battery state of charge neutral operation between the start and end of a drive cycle, the net electrical energy consumption from the battery requires to be zero. An optimization algorithm can be developed and calibrated in different ways to achieve net zero battery energy over the cycle. For instance, the engine can be operated at powers higher than the power of the drive cycle to charge the battery. This accumulated energy can be used for all-electric propulsion by turning off the engine.

The crashworthiness of body-in-white (BIW) plays a vital role in full vehicle crash performance. The structural integrity of BIW is controlled via strength of the spot welds and adhesives that are the primary entities to join sheet metal. The number of welds and amount of adhesives in the entire BIW directly affects the cost and the cycle time of the BIW; which makes them a good candidate for optimization. However optimization of the welds and/or adhesives not only reduces the number of connections but also provides the opportunity to improve the structural performance and mass saving by placing them optimally for the structural responses. This paper discusses the optimization of full vehicle structural performance for the small overlap crash event using the length of adhesives in the BIW as parameters. Included in the study were length of the adhesives and gage variables, defined in the front-end structure of the vehicle.