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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.

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.

Warranty forecasting of repairable systems is very important for manufacturers of mass produced systems. It is desired to predict the Expected Number of Failures (ENF) after a censoring time using collected failure data before the censoring time. Moreover, systems may be produced with a defective component resulting in extensive warranty costs even after the defective component is detected and replaced with a new design. In this paper, we present a forecasting method to predict the ENF of a repairable system using observed data which is used to calibrate a Generalized Renewal Processes (GRP) model. Manufacturing of products may exhibit different production patterns with different failure statistics through time. For example, vehicles produced in different months may have different failure intensities because of supply chain differences or different skills of production workers, for example.

For the designing of world class vehicles, ride comfort is one of the criteria that vehicle manufacturers are constantly trying to improve. The automotive seating system is an important sub-system in a vehicle that contributes to the ride comfort of the vehicle occupants. Seat vibrations are perceived by the occupants and make them feel uncomfortable during driving conditions. These vibrations are majorly transferred from engine and road excitation loads. For road excitation loads, the road testing may not be accurately repeatable, and measurements based on four post shakers are used to assess the discomfort. The major challenges for the vehicle manufactures is the availability of physical prototypes at an early stage of vehicle development and any changes in the design due to test validation leads to huge cost and time.

Use of parametric approach to optimize CAE models for various objectives is a common practice these days. In addition to load members, the connection entities such as welds and adhesives play an important role in overall performance matrix. Hence adding the connection entities to the pool of design variables during an optimization exercise provide additional opportunity for design exploration. The method presented in this paper offers a unique approach to parameterize adhesive lines by evaluating the possibility of using structural adhesives as intermittent patches rather than continuous lines. The paper discusses two optimization studies 1) structural adhesive patches along with spot weld pitch as design variables, and 2) structural adhesive patches with gage variables. These studies include the Body in White (BiW) and Trimmed Body in White (TBiW) assessments.

Cylinder deactivation has been in use for several years resulting in a sizable fuel economy advantage for V8-powered vehicles. The size of the fuel-economy benefit, compared to the full potential possible, is often limited due to the amount of usable torque available in four-cylinder-mode being capped by Noise, Vibration, and Harshness (NVH) sensitivities of various rear-wheel-drive vehicle architectures. This paper describes the application and optimization of active vibration absorbers as a system to attenuate vibration through several paths from the powertrain-driveline into the car body. The use of this strategy for attenuating vibration at strategic points is shown to diminish the need for reducing the powertrain source amplitude. This paper describes the process by which the strategic application of these devices is developed in order to achieve the increased usage of the most fuel efficient reduced-cylinder-count engine-operating-points.

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.

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.

The wet clutch system (WCS) is a complex combination of friction plates, separator plates and fluid (lubricant). The basic function of the WCS is to transfer torque under various operating conditions such as slipping, shifting, start/launch and/or torque converter clutch (TCC) operation. Under these conditions the slope of the coefficient of friction (μ or COF) versus slip speed (μ-v) curve must be positive to prevent shudder of the WCS, a highly undesirable condition in the lubricated friction system. An extended durability duty cycle test procedure is required to evaluate the WCS during which the μ-v curve is monitored for a negative slope, a condition indicating the potential for shudder. The friction plates, separator plates, and lubricant must be tested together and remain together during the test to be properly evaluated as a WCS.

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 paper will explore the effect that non-constant function CD (as observed during wind tunnel testing) would have on the coastdown derived drag coefficient and other regulatory drive cycles. It is common in wind tunnel testing to observe road vehicle drag coefficients that vary with speed. These varying CD values as a function of velocity will be expressed as CD(V) in this paper. Wind tunnel testing for product development is generally conducted at 110 km/h (68.3 mph) which are similar speeds and typical of the United States (US), European, and Asian highway speeds. Reported values of CD are generally gathered at these speeds. However, coastdown testing by definition takes place over a large range of speeds mostly lower than the wind tunnel test speeds. This paper will explore the effect that six typical functions of CD(V) have on the coastdown derived CD. One of the six functions is a constant, to represent a wind tunnel reported CD.

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.

Significant reduction in Nitrogen Oxide (NOx) emissions will be required to meet LEV III Emissions Standards for Light Duty Diesel passenger vehicles (LDD). As such, Original Equipment Manufacturers (OEMs) are exploring all possible aftertreatment options to find the best balance between performance, robustness and cost. The primary technology adopted by OEMs in North America to achieve low NOx levels is Selective Catalytic Reduction (SCR) catalyst. The critical parameters needed for SCR to work properly are: an appropriate reductant such as ammonia (NH3) typically provided as urea, adequate operating temperatures, and optimum Nitrogen Dioxide (NO2) to NOx ratios (NO2/NOx). The NO2/NOx ratio is mostly influenced by Precious Group Metals (PGM) containing catalysts located upstream of the SCR catalyst. Different versions of zeolite based SCR technologies are available on the market today and these vary in their active metal type (iron, copper, vanadium), and/or zeolite type.

Vehicle suspension parts are subjected to variable road loads, manufacturing process variation and high installation loads in assembly process. These parts must be robust to usage conditions to function properly in the field. Design for Six Sigma (DFSS) tools and Taguchi Method were used to optimize initial rear suspension trailing arm design. Project identified key control factor/design parameters, to improve part robustness at the lowest cost. Optimized design performs well under higher road loads and meets stringent durability requirements. This paper evokes use of Taguchi Method to design robust rear suspension trailing arm and study effect of selected design parameters on robustness, stress level/durability and part cost.

Threaded fasteners or bolted joints are used extensively in automotive assemblies. There are standard procedures to evaluate joint performance under block cycles or road loads. The deciding load case for such joint design is slippage analysis of the joint. There are studies done to evaluate the theoretical and experimental behavior of these joints. There are different ways of understanding the interaction between the bolt and the nut under different loading scenarios. However, none have provided a satisfactory method of quantifying bolt loosening or loss of clamp load under cyclic loading, where no slippage is observed. Under varying loads, initial relaxation of the joint is followed by a loss of clamping load. Below a critical value, complete loss of clamping load progresses very rapidly and this results in a loose joint.

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.