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Proper orthogonal decomposition (POD) has been proposed as an approach to analyze complex turbulent flows in piston engines, and as a basis for making quantitative, objective comparisons between in-cylinder velocity fields obtained using high-speed optical diagnostics (e.g., particle-image velocimetry - PIV) and numerical simulations (e.g., large-eddy simulation - LES). Here we explore several POD variants that can be used to analyze statistically nonstationary flows in time-varying domains, such as piston engines, in a well-defined and relatively simple geometric configuration. Systematic parametric studies are performed, including sensitivities of POD mode structure and mode convergence rate to spatial and temporal resolution. The use of POD to identify and quantify cycle-to-cycle flow variations is explored, and the ability of POD to distinguish between organized and disorganized flows is demonstrated.

This project is one component of a broader effort whose ultimate goal is to provide CFD-based tools that can be used to optimize the design of urea SCR NOx aftertreatment systems for heavy-duty diesel engines. Here the focus is on predicting the distributions of key chemical species (ammonia, in particular) at the inlet to the catalysts. Two aspects of the physical models have been emphasized: the multi-phase models, and the gas-phase chemistry models. A hierarchy of four simplified geometric configurations has been used for model development and parametric studies, and to establish the appropriate level of physical modeling and numerical fidelity required. The resulting physical and numerical parameters then have been used to model a production SCR system. Initial quantitative comparisons with experimental measurements are encouraging.

In an Internal Combustion (IC) Engine, the exhaust manifold has the primary function of channeling products of combustion from cylinder head runners to the emissions system through a collector. Exhaust manifolds must endure severe thermal loads and high strain caused by channeling extremely hot gases and fastener loads, respectively. The combination of these two loads can lead to Thermomechanical Fatigue (TMF) failures after repeated operational cycles if they are not assessed and addressed adequately during the design process. Therefore, it is vital to have a methodology in place to evaluate the life of an engine component (such as the exhaust manifold) using a TMF damage prediction model. To accomplish this, spatial temperature prediction and maximum value attained, as well as temporal distribution, are the most important input conditions.

The availability of computational resources has enabled an increased utilization of Design of Experiments (DoE) and metamodeling (response surface generation) for large-scale optimization problems. Despite algorithmic advances however, the analysis of systems such as water jackets of an automotive engine, can be computationally demanding in part due to the required accuracy of metamodels. Because the metamodels may have many inputs, their accuracy depends on the number of training points and how well they cover the entire design (input) space. For this reason, the space-filling properties of the DoE are very important. This paper utilizes a new group-based DoE algorithm with space-filling groups of points to construct a metamodel. Points are added sequentially so that the space-filling properties of the entire group of points is preserved. The addition of points is continuous until a specified metamodel accuracy is met.

The production of multi-mode power-split hybrid vehicles has been implemented for some years now and it is expected to continually grow over the next decade. Control strategy still represents one of the most challenging aspects in the design of these vehicles. Finding an effective strategy to obtain the optimal solution with light computational cost is not trivial. In previous publications, a Power-weighted Efficiency Analysis for Rapid Sizing (PEARS) algorithm was found to be a very promising solution. The issue with implementing a PEARS technique is that it generates an unrealistic mode-shifting schedule. In this paper, the problematic points of PEARS algorithm are detected and analyzed, then a solution to minimize mode-shifting events is proposed. The improved PEARS algorithm is integrated in a design methodology that can generate and test several candidate powertrains in a short period of time.

This paper focuses on the conjugate heat transfer analysis of an I4 engine, and discusses optimization of the coolant passages in engine coolant jackets. Direct Optimization approach integrates an optimizer with the numerical solver. This method of optimization is compared with a metamodel-based optimization in which a metamodel is generated to aid in finding an optimal design. The direct optimization and metamodel approaches are compared in terms of their accuracy, and execution time.

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.

This experimental study involves optimization of the scheduling of diesel post injections to reduce soot emissions from a light-duty diesel engine. Previous work has shown that certain post injection schedules can reduce engine-out soot emissions when compared to conventional injection schedules for the same engine load. The purpose of this study is to investigate the impact of post injection scheduling for a range of engine conditions on a light duty multicylinder turbodiesel engine (1.9L GM ZDTH). For each engine operating condition, a test grid was developed so that only two variables (post injection duration and the commanded dwell time between main injection and post injection) were varied, with all other conditions held constant, in order to isolate the effects of the post injection schedule. Results have identified two distinct regimes of post injection schedules that reduce soot emissions.

In a passenger car, suspension link bushings, engine and transmission mount bushings and bump-stops are made of elastomeric materials, to maximize the durability and comfort. Thus, deformation behavior of rubber and its durability is important for product design and development. In virtual engineering, simulating rubber fatigue is a complex exercise, since it needs right modeling strategy and coupon based testing material data. Principal stretches based Ogden model is used to characterize the hyper elastic deformation behavior of natural rubber. Fatigue crack growth approach used here for the fatigue analysis. Engine torque strut mount is used to control the engine and transmission fore aft motion and it is connected between body and Powertrain (PT) system. Powertrain events are predominant for damage contribution to mount failure. So, it is important to predict fatigue life of mount elastomer bushing under Powertrain loading.

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.

One of the building blocks of the Stellantis hybrid powertrain embedded control software computes the maximum and minimum values of objective functions, such as output torque, as a function of engine torque, hybrid motor torque and other variables. To test such embedded software, an offline reference function was created. The reference function calculates the ideal minimum and maximum values to be compared with the output of the embedded software. This article presents the offline reference function with an emphasis on mathematical novelties. The reference function computes the minimum and maximum points of a linear objective function as a function of six independent variables, subject to 42 linear and two nonlinear constraints. Concave domains, curved surfaces, disjoint domains and multiple local extremum points challenge the algorithm. As a theorem, the conditions and methods for running trigonometric calculations in 6D Euclidean space are presented.

The proliferation and increased complexity of electrified powertrains presents a challenge to the associated controls development. This paper outlines the strategy of common supervisory and domain torque management for such powertrains. The strategy covers the multitude of powertrain architectures that exist in the market today while maintaining the fundamental pillars of physics-based torque controls, state-of-the-art optimization methodologies, and common-core hybrid system constraints. The electrified powertrain torque controls that Stellantis LLC. uses include key constituents such as optimization of powertrain state that relate to optimum engine speed and transmission gear, optimization of engine and motor torques, engine start-stop management, and hybrid shift execution which manages powertrain state transitions by interacting with various external transmission systems. The common backbone of these constituents are the dynamic/kinematic equations of the powertrain.

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.

More stringent Federal emission regulations and fuel economy requirements have driven the automotive industry toward more efficient vehicle thermal management systems to best utilize the heat produced from burning fuel and improve driveline efficiency. The greatest part of the effort is directed toward the hybridization of automotive transmission systems. The efficiency and durability of hybrid powertrain depends on the heat generation in electric motors and their interactions among each other, ambient condition, the cooling system and the transmission component configuration. These increase the complexity of motor temperature prediction as well as the computational cost of running a conjugate heat-transfer based CFD analysis. In this paper, 1D physics based thermal model is developed which allows rapid and accurate component-wise temperature estimation of the electric motor during both steady-state and transient driving cycles.

Modern powertrains are highly complex systems whose development requires careful tuning of hundreds of parameters, called calibrations. These calibrations determine essential vehicle attributes such as performance, dynamics, fuel consumption, emissions, noise, vibrations, harshness, etc. This paper presents a methodology for automatic generation of calibrations for a powertrain-abstraction software module within the powertrain software of hybrid electric vehicles. This module hides the underlying powertrain architecture from the remaining powertrain software. The module encodes the powertrain’s torque-speed equations as calibrations. The methodology commences with modeling the powertrain in MapleSim, a multi-domain modeling and simulation tool. Then, the underlying mathematical representation of the modeled powertrain is generated from the MapleSim model using Maple, MapleSim’s symbolic engine.

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.

The application of Computational Fluid Dynamics (CFD) for three-dimensional (3D) combustion analysis coupled with detailed chemistry in engine development is hindered by its expensive computational cost. Chemistry computation may occupy as much as 90% of the total computational cost. In the present paper, a new two-step iso-octane combustion model was developed for spark-ignited (SI) engine to maximize computational efficiency while maintaining acceptable accuracy. Starting from the model constants of an existing global combustion model, the new model was developed using an approach based on sensitivity analysis to approximate the results of a reference skeletal mechanism. The present model involves only five species and two reactions and utilizes only one uniform set of model constants. The validation of the new model was performed using shock tube and real SI engine cases.

With continued industry focus on reducing parasitic transmission and driveline losses, detailed studies are required to quantify potential enablers to improve vehicle fuel economy. Investigations were undertaken to understand the influence of lower viscosity Automatic Transmission Fluids (ATF) on transmission efficiency as compared with conventional fluids. The objectives of this study were to quantify the losses of lower viscosity ATF as compared with conventional ATF, and to understand the influence of ATF properties including viscosities, base oil types, and additive packages on fuel efficiency. The transmission efficiency investigations were conducted on a test bench following a vehicle-based break-in of the transmission using a prescribed drive cycle on a chassis dynamometer. At low temperature, the lower viscosity ATF showed a clear advantage over the conventional ATF in both spin loss and loaded efficiency evaluations.

An Air intake system (AIS) is a duct system which leads the airflow going into the internal combustion engine. Combustion requires oxygen, and the more oxygen is provided into the combustion process the more power it will produce. The lower the air temperature, the higher its density, and hence there is more oxygen in a unit volume. The quality of air entering engine can be measured with the air temperature. AIS design and routing influence the air charge temperature (ACT) at intake manifold runners and ACT is normally measured at AIS throttle body in reality. Higher ACT lead to inefficient combustion and can lead to spark retard. Optimization of AIS designs and reduction of ACT can improve engine performance and vehicle fuel economy. High ACT can be a result of two different phenomena: Recirculation - Hot air from the underhood environment ingested into the dirty side of the air intake system.

Valvetrain dynamics modeling and engine combustion modeling are often carried out independently. As a result, the interaction between these two physical responses may not be accurately assessed. The objective of this work is to understand the impact that robust valve timing simulations, implemented using a fully coupled valve train dynamics and engine performance model, have on engine performance prediction. The integrated simulation and detailed technical approach are discussed through the presentation of an example implementation. An I4 engine model is developed in which engine performance and valvetrain dynamics modeling are coupled. A benefit of this multi-physics approach is that it reduces reliance on empirically derived estimates of valve lash in favor of physical modeling of engine valvetrain dynamics that predicts lash during engine performance modeling.