Search Results

Present work investigates the relationship between the combustion parameters of a well-known ECN heavy-duty nozzle called Spray D and marine-size nozzles. The study is carried out in OpenFOAM software within the framework of RANS turbulence modelling, using a flamelet based tabulation technique known as FGM to model the combustion. The large nozzles are tested in a constant volume chamber representative of marine engines, for which a CFD setup is validated against inert data in literature. The reacting results have been validated first with experimental data, initializing the domain with a highly reactive environment (23% oxygen) and engine-like swirl. Then, a less reactive initial condition was set up in the domain (15% oxygen) without swirl, to achieve a Spray D-like environment.

Methanol is one of the most promising fuels for the decarbonization of the off-road and transportation sectors. Although methanol is typically seen as an alternative fuel for spark ignition engines, mixing-controlled compression ignition (MCCI) combustion is typically preferred in most off-road and medium-and heavy-duty applications due to its high reliability, durability and high-efficiency. In this paper, the potential of using ignition enhancers to enable methanol MCCI combustion was investigated. Methanol was blended with 2-ethylhexyl nitrate (EHN) and experiments were performed in a single-cylinder production-like diesel research engine, which has a displacement volume of 0.83 L and compression ratio of 16:1. The effect of EHN has been evaluated with three different levels (3%vol, 5%vol, and 7%vol) under low- and part-load conditions. The injection timing has been swept to find the stable injection window for each EHN level and load.

The pressure of energy transition and sustainable development has driven the rapid development of new energy vehicles (NEVs). Lithium-ion batteries (LIBs) are extensively utilized in NEVs because of their higher energy density, lower self-discharge rate, and environmental friendliness. Nevertheless, at subzero temperature environments, the electrochemical performance and available energy of LIBs are severely reduced, exhibiting significant charging difficulties, lifespan degradation, and safety issues. This performance degradation can contribute to the operational difficulties and safety hazards of NEVs. The purpose of this article is to provide a review of the challenges and limitations faced by LIBs in subzero temperature environments, as well as the development of subzero temperature LIBs from the cell level to the system level. Additionally, viable solutions to heat the battery by increasing the internal temperature are introduced.

A major concern for a high-power density, heavy-duty engine is the durability of its components, which are subjected to high thermal loads from combustion. The thermal loads from combustion are unsteady and exhibit strong spatial gradients. Experimental techniques to characterize these thermal loads at high load conditions on a moving component such as the piston are challenging and expensive due to mechanical limitations. High performance computing has improved the capability of numerical techniques to predict these thermal loads with considerable accuracy. High-fidelity simulation techniques such as three-dimensional computational fluid dynamics and finite element thermal analysis were coupled offline and iterated by exchanging boundary conditions to predict the crank angle-resolved convective heat flux and surface temperature distribution on the piston of a heavy-duty diesel engine.

Despite the widespread adoption of lithium-ion batteries in various applications such as energy storage, concerns related to thermal management have been persisting, primarily due to the heat generated during their operation and the associated adverse effects on its efficiency, safety, and lifetime. Hence, the thermal characterization of lithium-ion batteries is essential for optimizing the layout of the battery cells for a pack design and the corresponding thermal management system. This study focuses on an experimental investigation of heat generation of Li-ion batteries under different operating conditions, including charge-discharge rates, ambient temperatures, states of charge, and compressive pressure. The experiments were conducted using a custom-designed multifunctional calorimeter, enabling precise measurement of the heat generation rate of the battery and the entropy coefficient. The measured results have shown a good match with the calculated heat generation rate.

Fast charging of traction batteries in passenger cars enables comfortable travel with electric vehicles, even over longer distances, without having to oversize the installed batteries for everyday use. As an enabling technology for fast charging, Kautex presents the implementation of 2-phase immersion cooling, where the traction battery serves as an evaporator in a refrigeration process. The 2-phase immersion cooling enables very high heat transfer rates of 3400 W/m^2*K and at the same time maximizes temperature homogeneity within the battery pack at optimal battery operating temperature. Thus, heat loads at charging rates of more than 6C can be safely and permanently managed by the battery thermal system. The cooling performance of 2-phase immersion cooling can also successfully suppress thermal propagation inside a thermoplastic battery housing.

Concerns about climate change have significantly accelerated the process of vehicle electrification to improve the sustainability of the transportation sector. Increasing the adoption of electrified vehicles is closely tied to the advancement of reliable energy storage systems, with lithium-ion batteries currently standing as the most widely employed technology. One of the key technical challenges for reliability and durability of battery packs is the ability to accurately predict and control the temperature of the cells and temperature gradient between cells inside the pack. For this reason, accurate models are required to predict and control the cell temperature during driving and charging operations. This work presents a set of procedures tailored to characterize and measure the thermal properties in li-ion cells and modules.

The main objective of this paper is to describe the design, analysis and testing of a novel method of insulating the combustion chamber, which is key for efficiency demonstration on a new class of internal combustion engine (ICE). A recuperated split cycle engine (RSCE) has unique demands for heat loss reduction. In particular during the combustion event, to minimize the heat losses is a must to achieve high efficiency. The insulation is provided by a metal plate that is assembled into the cylinder head to line the combustion chamber surface. The design has been focused on reducing heat transfer surface area and exploiting contact gap thermal resistance between the upper surface of the plate and the cylinder head, thus reducing heat wasted to the coolant circuit. In this paper, the plate requirements, functions, design, analysis and test results from a research and development (R&D) program of a heavy duty (HD) recuperated split cycle engine are reported.

Baking ovens in the automotive paint shop are crucial to ensuring quality of paint curing and hence meet the corrosion protection targets in manufacturing process. Ovens are also among the most energy consuming processes in the entire paint shop. With the onset of Electric Vehicle revolution, original equipment manufacturers focus heavily on light weighting resulting in significant design changes to the body in white (BIW). This presents a challenge of achieving accurate curing in the existing ovens designed for the current and past generations of vehicles Using Computational fluid dynamics (CFD), this research intends to present a solution by minimizing the need for prototyping for design changes. Lattice Boltzmann Method (LBM) based thermal simulations are used to predict the curing behaviour on the BIW surface. The LBM based conjugated heat transfer simulations consider turbulence using a Large-Eddy Simulation (LES) approach and Boussinesq approximation.

Semiconductor devices in electric vehicle (EV) motor drive systems are considered the most fragile components with a high occurrence rate for open circuit fault (OCF). Various signal-based and model-based methods with explicit mathematical models have been previously published for OCF diagnosis. However, this proposed work presents a model-free machine learning (ML) approach for a single-switch OCF detection and localization (DaL) for a two-level, three-phase inverter. Compared to already available ML models with complex feature extraction methods in the literature, a new and simple way to extract OCF feature data with sufficient classification accuracy is proposed. In this regard, the inherent property of active thermal management (ATM) based model predictive control (MPC) to quantify the conduction losses for each semiconductor device in a power converter is integrated with an ML network.

The China Automotive Technology and Research Center (CATARC) has completed two new wind tunnels at its test centre in Tianjin, China: an aerodynamic/aeroacoustic wind tunnel (AAWT), and a climatic wind tunnel (CWT). The AAWT incorporates design features to provide both a very low fan power requirement and a very low background noise putting it amongst the quietest in the automotive world. These features are also combined with high flow quality, a full boundary layer control system with a 5-belt rolling road, an automated traversing system, and a complete acoustic measurement system including a 3-sided microphone array. The CWT, located in the same building as the AAWT, has a flexible nozzle to deliver 250 km/h with an 8.25 m2 nozzle, and 130 km/h with a 13.2 m2 nozzle. The temperature range of the CWT is -40 °C to +60 °C with a controlled humidity range of 5% to 95%. Additional integrated systems include a variable angle solar simulator array, and a rain and snow spray system.

Performances of battery electric vehicles (BEV) are affected by the thermal imbalance in the battery packs under driving cycles. BEV thermal management system (VTMS) should be managed efficiently for optimal energy consumption and cabin comfort. Temperature changes in the brick, module, and pack under the repeated transient cycles must be understood for model-based development. The authors conducted chassis dynamometer experiments on a fully electric small crossover sports utility vehicle (SUV) to address this challenge. A BEV is tested using a hub-type, 4-wheel motor chassis dynamometer with an air blower under the Worldwide Harmonized Light Vehicles Test Cycle (WLTC) and Federal Test Procedures (FTP) with various ambient temperatures. The mid-size BEV with dual-motor featured 80 thermocouples mounted on the 74-kWh battery pack, including the cells, upper tray, side cover, and pack cover.

The degradation rate of a Li-ion battery is a complex function of temperature and charge/discharge rates over its lifetime. There is obviously a keen interest in predictive electrochemical ageing models that account for known degradation mechanisms, primarily linked with the Solid Electrolyte Interface (SEI) formation and Li-plating, which are highly dependent on the cell temperature. Typically, such ageing models are formulated and employed at pack or cell level, neglecting intra-cell and cell-to-cell thermal and electrical non-uniformities. On the other hand, thermal management techniques can mitigate ageing by maintaining the battery pack within the desired temperature window either by cooling or heating. Inevitably, the cooling of the battery pack by conventional heat exchangers will introduce temperature non-uniformities that may in turn result in undesired intra-cell and/or cell-to-cell health non-uniformities.

The growing global adoption of electric vehicles (EVs) emphasizes the pressing need for a comprehensive understanding of thermal runaway in lithium-ion batteries. Prevention of the onset of thermal runaway and its subsequent propagation throughout the entire battery pack is one of the pressing challenges of lithium-ion batteries. In addition to generating excess heat, thermal runaway of batteries also releases hazardous flammable gases, posing risks of external combustion and fires. Most existing thermal runaway models in literature primarily focus on predicting heat release or the total amount of vent gas. In this study, we present a model capable of predicting both heat release and the transient composition of emitted gases, including CO, H2, CO2, and hydrocarbons, during thermal runaway events. We calibrated the model using experimental data obtained from an 18650 cell from the literature, ensuring the accuracy of reaction parameters.

Off-road diesel engines remain one of the most significant contributors to the overall oxides of nitrogen (NOX) inventory and the California Air Resources Board (CARB) has indicated that reductions of up to 90% from current standards may be necessary to achieve its air quality goals. In recognition of this, CARB has funded a program aimed at demonstrating emission control technologies for off-road engines. This program builds on previous efforts to demonstrate Low NOX technologies for on-road engines. The objective was to demonstrate technologies to reduce tailpipe NOX and particulate matter (PM) emissions by 90 and 75%, respectively, from the current Tier 4 Final standards. In addition, the emission reductions were to be achieved while also demonstrating a 5 to 8.6% carbon dioxide (CO2) reduction and remaining Greenhouse Gas (GHG) neutral with respect to nitrous oxide (N2O) and methane (CH4).

The high-efficiency dedicated hybrid engine (DHE) has led to increasingly complex challenges in engine thermal management. On one hand, the high compression ratio of up to 16:1 makes the engine more susceptible to knocking, necessitating meticulous thermal management to mitigate the potential sensitivity to metal temperature. On the other hand, extensive use of external cooled exhaust gas recirculation (EGR) helps reduce knocking and improve thermal efficiency, but it also raises temperature levels and requires additional cooling measures. For the 1.5L DHE developed by SAIC Motor, a split cooling structure was employed in the engine cooling system design, with the cylinder head water jacket and cylinder block water jacket arranged in parallel and equipped with different coolant outlets. By utilizing a dual thermostat to control flow, this design allows for adjustable flow distribution, providing effective cooling to the cylinder head while reducing cooling to the cylinder block.

Turbulent jet ignition (TJI) combustion using pre-chamber ignition can accelerate the combustion speed in the cylinder and has garnered growing interest in recent years. However, it is complicated for the optimization of the pre-chamber structure and combustion system. This study investigated the effects of the pre-chamber structure and the intake ports on the combustion characteristics of a gasoline engine through CFD simulation. Spark ignition (SI) combustion simulation was also conducted for comparison. The results showed that the design of the pre-chamber that causes the jet flame colliding with walls severely worsen the combustion, increasing the knocking intendency, and decrease the thermal efficiency. Compared with SI combustion mode, the TJI combustion mode has the higher heat transfer loss and lower unburned loss. The well-optimized pre-chamber can accelerate the flame propagation with knock suppression.

To meet the ever-increasing demands of the engineering industry, novel approaches to design optimization are essential, especially in fast-paced production environments. Conventional CAD and simulation tools often struggle to keep up with the complexity and speed required for designing critical components. In this context, leveraging Deep Learning technologies presents a promising solution by integrating knowledge from simulations and designs to drastically accelerate product development. With the drive for Electrification, conventional power electronics and systems are becoming more energy dense and hence requires compact and efficient thermal management solutions. Higher energy density is attributed to high power electrical components fitted in packs with shrinking characteristic dimensions and hence needs more efficient and compact thermal management solutions.

A need to develop a cooling method with high cooling performance like jet impingement is increased as high power of an inverter is required. Jet Impingement on the dimpled plate would increase thermal performance than that of flat plate. Many previous researchers have dealt with the multi jet impingement on flat plate and some results of the study on dimpled plate evaluate the effect on heat transfer coefficients on several limited cases, making it difficult to apply them to inverter designs. Therefore, in this paper, heat transfer performance, pressure drop, and robustness at micro-scale of jet impingement on the dimpled plate were investigated in detail and the correlations of each performance were proposed. Finally, the optimal design was presented. The cooling performance was influenced by the jet array and the effect of depth and width of the dimples.

The transition towards electrification in commercial vehicles has received more attention in recent years. This paper details the conversion of a production Medium-Duty class-5 commercial truck, originally equipped with a gasoline engine and 10-speed automatic transmission, into a battery electric vehicle (BEV). The conversion process involved the removal of the internal combustion engine, transmission, and differential unit, followed by the integration of an ePropulsion system, including a newly developed dual-motor beam axle that propels the rear wheels. Other systems added include an 800V/99 kWh battery pack, advanced silicon carbide (SiC) inverters, an upgraded thermal management system, and a DC fast charging system. A key part of the work was the development of the propulsion system controls, which prioritized drivability, NVH suppression, and energy optimization.