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With the increasing demand for Battery Electric Vehicles (BEVs) capable of extended mileage, optimizing their efficiency has become paramount for manufacturers. However, the challenge lies in balancing the need for climate control within the cabin and precise thermal regulation of the battery, which can significantly reduce a vehicle's driving range, often leading to energy consumption exceeding 50% under severe weather conditions. To address these critical concerns, this study embarks on a comprehensive exploration of the impact of weather conditions on energy consumption and range for the 2019 Nissan Leaf Plus. The primary objective of this research is to enhance the understanding of thermal management for BEVs by introducing a sophisticated thermal management system model, along with detailed thermal models for both the battery and the cabin.

The autoignition chemistry of fuels depends on the pressure, temperature, and time history that the fuel-air mixture experiences during the compression stroke. While piezoelectric pressure transducers offer excellent means of pressure measurement, temperature measurements are not commonly available and must be estimated. Even if the pressure and temperature at the intake and exhaust ports are measured, the residual gas fraction (RGF) within the combustion chamber requires estimation and greatly impacts the temperature of the fresh charge at intake valve closing. This work replaced the standard D1 Detonation Pickup of a CFR engine with a rapid sampling valve to allow for in-cylinder gas sampling at defined crank-angle times during the compression stroke. The extracted cylinder contents were captured in an emissions sample bag and its composition was subsequently analyzed in an AVL i60 emissions bench.

The current research octane number (RON) and motor octane number (MON) gasoline tests are inadequate for describing the auto-ignition reactivity of fuels in homogeneous charge compression ignition (HCCI) combustion. Intake temperature and engine speed are two important parameters when trying to understand the fuel auto-ignition reactivity in HCCI combustion. The objective of this study was to understand the effect of high intake temperature (between 100 and 200 °C) and engine speed (600 and 900 rpm) on the auto-ignition HCCI reactivity ratings of fuels using an instrumented Cooperative Fuel Research (CFR) engine. The fuels used for this study included blends of iso-octane/n-heptane, toluene/n-heptane, ethanol/n-heptane, and gasolines with varying chemical compositions and octane levels. The CFR engine was operated at 600 and 900 rpm with an intake pressure of 1.0 bar and an excess air ratio (lambda) of 3.

In this work, a high temperature (HT) homogeneous charge compression ignition (HCCI) critical compression ratio (cCR) was defined as the compression ratio which resulted in HCCI combustion with a crank angle location of 50% fuel burned (CA50) of 3.0 degrees after top dead center (aTDC) while operating at an equivalence ratio of 0.33 (λ = 3), an intake pressure of 1.0 bar (naturally aspirated), an intake temperature of 473 K (200°C), and an engine speed of 600 rpm. Using a Cooperative Fuel Research engine, the HT HCCI cCR of seven alcohol fuels were experimentally determined and found to be ordered as follows (ordered from least reactive to most reactive): isopropanol > sec-butanol > methanol ≈ ethanol ≈ n-propanol ≈ isobutanol > n-butanol. The HT HCCI cCR for the alcohol fuels correlated well with experimental HCCI data from a modern gasoline direct injection (GDI) engine architecture with a pent-roof head and a rebreathe valvetrain.

Multi-mode combustion strategies may provide a promising pathway to improve thermal efficiency in light-duty spark ignition (SI) engines by enabling switchable combustion modes, wherein an engine may operate under advanced compression ignition (ACI) at low load and spark-assisted ignition at high load. The extension from the SI mode to the ACI mode requires accurate control of intake charge conditions, e.g., pressure, temperature and equivalence ratio, in order to achieve stable combustion phasing and rapid mode-switches. This study presents results from computational fluid dynamics (CFD) analysis to gain insights into mixture charge formation and combustion dynamics pertaining to auto-ignition processes. The computational study begins with a discussion of thermal wall boundary condition that significantly impacts the combustion phasing.

The study of spray-wall interaction is of great importance to understand the dynamics that occur during fuel impingement onto the chamber wall or piston surfaces in internal combustion engines. It is found that the maximum spreading length of an impinged droplet can provide a quantitative estimation of heat transfer and energy transformation for spray-wall interaction. Furthermore, it influences the air-fuel mixing and hydrocarbon and particle emissions at combusting conditions. In this paper, an analytical model of a single diesel droplet impinging on the wall with different inclined angles (α) is developed in terms of βm (dimensionless maximum spreading length, the ratio of maximum spreading length to initial droplet diameter) to understand the detailed impinging dynamic process.

While experimental data measured directly on the engine are very valuable, there is a limitation of what measurements can be made without modifying the engine or the process that is being investigated, such as cylinder temperature. In order to supplement the experimental results, a Three Pressure Analysis (TPA) GT-Power model of the Cooperative Fuel Research (CFR) engine was previously developed and validated for estimating cylinder temperature and residual fraction. However, this model had only been validated for normal and knocking spark ignition (SI) combustion with RON-like intake conditions (naturally aspirated, <52 °C). This work presents improvements made to the GT-Power model and the expansion of its use for HCCI combustion. The burn rate estimation sub-model was modified to allow for low temperature heat release estimation and compression ignition operation.

Diesel-fueled, heavy-duty engines are critical to global economies, but unfortunately they are currently coupled to the rising price and challenging emissions of Diesel fuel. Public awareness and increasingly stringent emissions standards have made Diesel OEMs consider possible alternatives to Diesel, including electrification, fuel cells, and spark ignition. While these technologies will likely find success in certain market segments, there are still many applications that will continue to require the performance and liquid-fueled simplicity of Diesel-style engines. Three-way catalysis represents a possible low-cost and highly-effective pathway to reducing Diesel emissions, but that aftertreatment system has typically been incompatible with Diesel operation due to the prohibitively high levels of soot formation at the required stoichiometric fuel-air ratios. This paper explores a possible method of integrating three-way catalysis with Diesel-style engine operation.

The CFR engine is the widely accepted platform to test standard Research Octane Number (RON) and Motored Octane Number (MON) for determining anti-knock characteristics of motor fuels. With increasing interest in engine downsizing, up-torquing, and alternative fuels for modern spark ignition (SI) engines, there is a need to better understand the conditions that fuels are subjected to in the CFR engine during octane rating. To take into account fuel properties, such as fuel heat of vaporization, laminar flame speed and auto-ignition chemistry; and understand their impacts on combustion knock, it is essential to estimate accurate cylinder conditions. In this study, the CFR F1/F2 engine was modeled using GT-Power with the Three Pressure Analysis (TPA) and the model was validated for different fuels and engine conditions.

This study presents estimates for measurement uncertainties for a Homogenous Charge Compression Ignition (HCCI)/Low-Temperature Gasoline Combustion (LTGC) engine testing facility. A previously presented framework for quantifying those uncertainties developed uncertainty estimates based on the transducers manufacturers’ published tolerances. The present work utilizes the framework with improved uncertainty estimates in order to more accurately represent the actual uncertainties of the data acquired in the HCCI/LTGC laboratory, which ultimately results in a reduction in the uncertainty from 30 to less than 1 kPa during the intake and exhaust strokes. Details of laboratory calibration techniques and commissioning runs are used to constrain the sensitivities of the transducers relative to manufacturer supplied values.

Simulation of chemical kinetic processes in combustion engine environments has become ubiquitous towards the understanding of combustion phenomenology, the evaluation of controlling parameters, and the design of configurations and/or control strategies. Such calculations are not free from error however, and the interpretation of simulation results must be considered within the context of uncertainties in the chemical kinetic model. Uncertainties arise due to structural issues (e.g., included/missing reaction pathways), as well as inaccurate descriptions of kinetic rate parameters and thermochemistry. In fundamental apparatuses like rapid compression machines and shock tubes, computed constant-volume ignition delay times for simple, single-component fuels can have variations on the order of factors of 2-4.

A computational fluid dynamics (CFD) guided combustion system optimization was conducted for a heavy-duty compression-ignition engine with a gasoline-like fuel that has an anti-knock index (AKI) of 58. The primary goal was to design an optimized combustion system utilizing the high volatility and low sooting tendency of the fuel for improved fuel efficiency with minimal hardware modifications to the engine. The CFD model predictions were first validated against experimental results generated using the stock engine hardware. A comprehensive design of experiments (DoE) study was performed at different operating conditions on a world-leading supercomputer, MIRA at Argonne National Laboratory, to accelerate the development of an optimized fuel-efficiency focused design while maintaining the engine-out NOx and soot emissions levels of the baseline production engine.

In this paper, a framework for estimating experimental measurement uncertainties for a Homogenous Charge Compression Ignition (HCCI)/Low-Temperature Gasoline Combustion (LTGC) engine testing facility is presented. Detailed uncertainty quantification is first carried out for the measurement of the in-cylinder pressure, whose variations during the cycle provide most of the information for performance evaluation. Standard uncertainties of other measured quantities, such as the engine geometry and speed, the air and fuel flow rate and the intake/exhaust dry molar fractions are also estimated. Propagating those uncertainties using a Monte Carlo simulation and Bayesian inference methods then allows for estimation of uncertainties of the mass-average temperature and composition at IVC and throughout the cycle; and also of the engine performances such as gross Integrated Mean Effective Pressure, Heat Release and Ringing Intensity.

Heat loss through wall boundaries play a dominant role in the overall performance and efficiency of internal combustion engines. Typical engine simulations use constant temperature wall boundary conditions [1, 2, 3]. These boundary conditions cannot be estimated accurately from experiments due to the complexities involved with engine combustion. As a result, they introduce a large uncertainty in engine simulations and serve as a tuning parameter. Modeling the process of heat transfer through the solid walls in an unsteady engine computational fluid dynamics (CFD) simulation can lead to the development of higher fidelity engine models. These models can be used to study the impact of heat loss on engine efficiency and explore new design methodologies that can reduce heat losses. In this work, a single cylinder diesel engine is modeled along with the solid piston coupled to the fluid domain.

Fan and fan-shroud design is critical for underhood air flow management. The objective of this work is to demonstrate a method to optimize fan-shroud shape in order to maximize cooling air mass flow rates through the heat exchangers using the Adjoint Solver in STAR-CCM+®. Such techniques using Computational Fluid Dynamics (CFD) analysis enable the automotive/transport industry to reduce the number of costly experiments that they perform. This work presents the use of CFD as a simulation tool to investigate and assess the various factors that can affect the vehicle thermal performance. In heavy-duty trucks, the cooling package includes heat exchangers, fan-shroud, and fan. In this work, the STAR-CCM+® solver was selected and a java macro built to run the primal flow and the Adjoint solutions sequentially in an automated fashion.

It is widely understood that cold ambient temperatures negatively impact vehicle system efficiency. This is due to a combination of factors: increased friction (engine oil, transmission, and driveline viscous effects), cold start enrichment, heat transfer, and air density variations. Although the science of quantifying steady-state vehicle component efficiency is mature, transient component efficiencies over dynamic ambient real-world conditions is less understood and quantified. This work characterizes wheel assembly efficiencies of a conventional and electric vehicle over a wide range of ambient conditions. For this work, the wheel assembly is defined as the tire side axle spline, spline housing, bearings, brakes, and tires. Dynamometer testing over hot and cold ambient temperatures was conducted with a conventional and electric vehicle instrumented to determine the output energy losses of the wheel assembly in proportion to the input energy of the half-shafts.

Understanding the short-lived structure of the plasma that forms between the electrodes of a spark plug is crucial to the development of improved ignition models for SI engines. However, measuring the amount of energy deposited in the gas directly and non-intrusively is difficult, due to the short time scales and small length scales involved. The breakdown of the spark gap occurs at nanosecond time scales, followed by an arc phase lasting a few microseconds. Finally, a glow discharge phase occurs over several milliseconds. It is during the arc and glow discharge phases that most of the heat transfer from the plasma to the electrodes and combustion gases occurs. Light emission can be used to measure an average temperature, but micron spatial resolution is required to make localized measurements.

The importance of radiative heat transfer on the combustion and soot formation characteristics under nominal ECN Spray A conditions has been studied numerically. The liquid n-dodecane fuel is injected with 1500 bar fuel pressure into the constant volume chamber at different ambient conditions. Radiation from both gas-phase as well as soot particles has been included and assumed as gray. Three different solvers for the radiative transfer equation have been employed: the discrete ordinate method, the spherical-harmonics method and the optically thin assumption. The radiation models have been coupled with the transported probability density function method for turbulent reactive flows and soot, where unresolved turbulent fluctuations in temperature and composition are included and therefore capturing turbulence-chemistry-soot-radiation interactions. Results show that the gas-phase (mostly CO2 ad H2O species) has a higher contribution to the net radiation heat transfer compared to soot.

This work involves modeling internal and near-nozzle flows of a gasoline direct injection (GDI) nozzle. The Engine Combustion Network (ECN) Spray G condition has been considered for these simulations using the nominal geometry of the Spray G injector. First, best practices for numerical simulation of the two-phase flow evolution inside and the near-nozzle regions of the Spray G injector are presented for the peak needle lift. The mass flow rate prediction for peak needle lift was in reasonable agreement with experimental data available in the ECN database. Liquid plume targeting angle and liquid penetration estimates showed promising agreement with experimental observations. The capability to assess the influence of different thermodynamic conditions on the two-phase flow nature was established by predicting non-flashing and flashing phenomena.

It is beneficial but challenging to operate spark-ignition engines under highly lean and dilute conditions. The unstable ignition behavior can result in downgraded combustion performance in engine cylinders. Numerical approach is serving as a promising tool to identify the ignition requirements by providing insight into the complex physical/chemical phenomena. An effort to simulate the early stage of flame kernel initiation in lean and dilute fuel/air mixture has been made and discussed in this paper. The simulations are set to validate against laboratory results of spark ignition behavior in a constant volume combustion vessel. In order to present a practical as well as comprehensive ignition model, the simulations are performed by taking into consideration the discharge circuit analysis, the detailed reaction mechanism, and local heat transfer between the flame kernel and spark plug.