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Predicting and preventing combustion anomalies leads to safe and efficient operation of the hydrogen internal combustion engine. This research presents the application of three machine learning (ML) models – K-Nearest Neighbors (KNN), Random Forest (RF) and Logistic Regression (LR) – for the prediction of combustion anomalies in a hydrogen internal combustion engine. A small experimental dataset was used to train the models and posterior experiments were used to evaluate their performance and predicting capabilities (both in operating points -speed and load- within the training dataset and operating points in other areas of the engine map). KNN and RF exhibit superior accuracy in classifying combustion anomalies in the training and testing data, particularly in minimizing false negatives, which could have detrimental effects on the engine.

DC fast charging (DCFC) also referred to as L3 charging, is the fastest charging technology to replenish the drivable range of an electric vehicle. DCFC provides the convenience of faster charging time compared to L1 and L2 at the expense of potentially increased battery health degradation. It is known to accelerate battery capacity fade leading to reduced range and lifetime of the EV battery. While there are active efforts and several means to reduce the downsides of DCFC at cell chemistry level, this trade-off is still an important consideration for most battery cells in automotive propulsion applications. Since DCFC is a customer driven technology, informing drivers of the trade-off of each DCFC event can potentially result in better outcomes for the EV battery life. Traditionally, the driver is advised to limit DCFC events without providing quantifiable metrics to inform their decisions during EV charging.

Vehicle-to-everything (V2X) communication, primarily designed for communication between vehicles and other entities for safety applications, is now being studied for its potential to improve vehicle energy efficiency. In previous work, a 20% reduction in energy consumption was demonstrated on a 2017 Prius Prime using V2X-enabled algorithms. A subsequent phase of the work is targeting an ambitious 30% reduction in energy consumption compared to a baseline. In this paper, we present the Eco-routing algorithm, which is key to achieving these savings. The algorithm identifies the most energy-efficient route between an Origin-Destination (O-D) pair by leveraging information accessible through commercially available Application Programming Interfaces (APIs). This algorithm is evaluated both virtually and experimentally through simulations and dynamometer tests, respectively, and is shown to reduce vehicle energy consumption by 10-15% compared to the baseline over real-world routes.

This research investigates the energy savings achieved through eco-driving controls in connected and automated vehicles (CAVs), with a specific focus on the influence of powertrain characteristics. Eco-driving strategies have emerged as a promising approach to enhance efficiency and reduce environmental impact in CAVs. However, uncertainty remains about how the optimal strategy developed for a specific CAV applies to CAVs with different powertrain technologies, particularly concerning energy aspects. To address this gap, on-track demonstrations were conducted using a Chrysler Pacifica CAV equipped with an internal combustion engine (ICE), advanced sensors, and vehicle-to-infrastructure (V2I) communication systems, compared with another CAV, a previously studied Chevrolet Bolt electric vehicle (EV) equipped with an electric motor and battery.

With the aim of decarbonizing the vehicles fleet, the use of hydrogen is promising solution. Hydrogen is an energy carrier, carbon-free, with high calorific value and with no CO2 and HC emissions burning in ICE. Hydrogen use in spark ignition engines has already been extensively investigated and optimized. On the other hand, its use in compression ignition engines has been little developed and, therefore, there is a lack of information regarding the combustion in ultra-lean conditions, typical of diesel engines. Several applications employ dual fuel combustion for the easy management of the PFI injection system to be applied in addition to the DI Common Rail system. However, this mode suffers from several problems regarding the management of the maximum flow rate of hydrogen into the intake. In particular, to avoid throwing hydrogen into the exhaust, injection must be started after the valve crossing.

The use of hydrogen in internal combustion engines is an effective approach to significantly support the reduction of CO2 emissions from the transportation sector using technically affordable solutions. The use of direct injection is the most promising approach to fully exploit hydrogen potential as a clean fuel, while preserving targets in terms of power density and emissions. In this frame, the development of an effective combustion system largely relies on the hydrogen-air mixture formation process, so to adequately control the charge stratification to mitigate pre-ignitions and knock and to minimize NOx formation. Hence, improving capabilities of designing a correct gas jet-air interaction is of paramount importance. In this paper the analysis of the evolution of a high-pressure gas jet produced by a single-hole prototype injector operated with different pressure ratios is presented.

The combustion of fossil-based fuels in ICEs, resulting in a huge amount of greenhouse gases (GHG) and leading to an immense global temperature rise, are the root causes of the more stringent emission legislations to safeguard health and that encourage further investigations on alternative carbon-neutral fuels. In this respect, the hydrogen has been considered as one of the potential clean fuels because of its zero-carbon nature. The current development of hydrogen-based ICEs focuses on the direct injection (DI) strategy as it allows better engine efficiency than the port fuel injection one. The behavior of the fuel jet is a fundamental aspect of the in-cylinder air-fuel mixing ratio, affecting the combustion process, the engine performances, and the pollutants emissions. In the present study, comprehensive investigations on the hydrogen jet behavior, generated by a Compressed Hydrogen Gas (CHG) injector under different operative conditions, were performed.

Argon power cycle hydrogen engine is an internal combustion engine that employs argon instead of nitrogen of air as the working fluid, oxygen as the oxidizer, and hydrogen as the fuel. Since argon has a higher specific heat ratio than air, argon power cycle hydrogen engines have theoretically higher indicated thermal efficiencies according to the Otto cycle efficiency formula. However, argon makes the end mixture more susceptible to spontaneous combustion and thus is accompanied by a stronger knock at a lower compression ratio, thus limiting the improvement of thermal efficiency in engine operation. In order to suppress the limitation of knock on the thermal efficiency, this paper adopts a combination of experimental and simulation methods to investigate the effects of port water injection on the knock suppression and combustion characteristics of an argon power cycle hydrogen engine.

The Argon Power Cycle (APC) is a novel zero-emission closed-loop argon recirculating engine cycle which has been developed by Noble Thermodynamics Systems, Inc. It provides a significant gain in indicated thermal efficiency of the reciprocating engine by breathing oxygen and argon rather than air. The use of argon, a monatomic gas, greatly increases the specific heat ratio of the working fluid, resulting in a significantly higher ideal Otto cycle efficiency. This technology delivers a substantial improvement in reciprocating engine performance, maximizing the energy conversion of fuel into useful work. Combined Heat and Power (CHP) operating under the APC represents a promising solution to realize a net-zero-carbon future, providing the thermal energy that hard-to-electrify manufacturing processes need while at the same time delivering clean, dispatchable, and efficient power.

Compression ignition engine-based transportation is nowadays looking for cleaner combustion solutions. Among them, ducted fuel injection (DFI) is emerging as a cutting-edge technology due to its potential to drastically curtail engine-out soot emissions. Although the DFI capability to abate soot formation has been demonstrated both in constant-volume and optical engine conditions, its optimization and understanding is still needed for its exploitation on series production engines. For this purpose, computational fluid dynamics (CFD) coupled with low-cost turbulence models, like RANS, can be a powerful tool, especially in the industrial context. However, it is often challenging to obtain reliable RANS-based CFD simulations, especially due to the high dependence of the various state-of-the-art turbulence models on the case study.

The internal combustion engine (ICE) has long dominated the heavy-duty sector by using liquid fossil fuels such as diesel but global commitments by countries and OEMs to reduce lifecycle carbon dioxide (CO2) emissions has garnered interest in alternative fuels like hydrogen. Hydrogen is a unique gaseous fuel that contains zero carbon atoms and has desired thermodynamic properties of high energy density per unit mass and high flame speeds. However, there are challenges related to its adoption to the heavy-duty sector as a drop-in fuel replacement for compression ignition (CI) diesel combustion given its high autoignition resistance. To overcome this fundamental barrier, engine manufacturers are exploring dual fuel combustion engines by substituting a fraction of the diesel fuel with hydrogen which enables fuel flexibility when there is no infrastructure and retrofittability to existing platforms.

The conjugate heat transfer, which effectively integrates the heat conduction within the solid metal block of the so-called Water Spider Geometry (WSG) configuration and the fluid domain within it, is computationally investigated in the present work, allowing an accurate representation of the temperature conditions at the solid-fluid interface. The WSG configuration represents a specially configured tube geometry that effectively reproduces the flow behavior observed in cooling channels associated with Internal Combustion (IC) engines. The inherent high flow unsteadiness potential of the WSG flow configuration, resulting from the complex flow guidance involving phenomena such as flow impingement, bifurcation, multiple deflections and flow confluence, requires the application of a model capable of capturing turbulence fluctuations.

The global imperative to develop clean energy solutions has redirected research efforts towards highly efficient combustion engines with ultra-low emissions. This has prompted investigations into alternative combustion concepts, including Low Temperature Combustion (LTC), utilizing environmentally friendly fuels. Within the scope of our research project, we are primarily focused on the development of an innovative combustion concept known as Homogeneous Reactivity-Controlled Compression Ignition (hRCCI), which employs renewable fuels such as ethanol and 1-octanol for a serial hybrid powertrain. The lack of predictive simulations for this concept presents a significant challenge in optimizing the engine's operation. Most of the 1D system simulation models use a non-predictive combustion model for combustion simulations. Due to the dependence on auto-ignition chemistry, a chemistry based hRCCI combustion model for real time computation has been proposed with this work.

Hydrogen is anticipated to play a pivotal role as a green energy carrier in both heavy industry and transportation. Utilizing hydrogen directly in internal combustion engines (ICE) could offer several advantages compared to alternative technologies. To achieve this objective, a proper understanding of the physical mechanisms and dynamics involved in the injection of this fuel is needed. This study applied high-fidelity computational fluid dynamics (CFD) simulations to describe the flow characteristics of hydrogen injection using hollow- and single- and multi-solid-cone injectors and their effect on mixing quality and characteristics in a constant volume quiescent environment. A reference hollow-cone configuration was used to validate the model. The results indicate that solid-cone configurations achieve greater penetration due to the flow patterns they generate. However, an increase in the number of holes leads to reduced penetration length, projected area, and induced turbulence.

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.

Using the recycled waste oils are to be focused for the protection of environment by reducing the land pollution and disposal costs. This study is to use the recycled waste engine oil, waste cooking oil and waste plastic oil along with Bio-butanol from the waste cut vegetables and fruits. Initially, properties and solubility were tested for choosing a suitable blend for fueling into diesel engine from various proportions. These three blends from the base of three waste oils are then tested by modifying and standard engine operating parameters for performance. The properties tests results as 18% of waste engine oil (by volume) with bio-butanol, 16% of waste cooking oil (by volume) with bio- butanol and 24% of waste plastic oil (by volume) with bio-butanol are found competent for fueling engine. These blends produces low efficiency in lower brake powers and the emissions of smoke, hydrocarbons and carbon monoxide are also higher during the operation under standard parameters.

The majority of transportation systems have continued to be powered by the internal combustion engine and fossil fuels. Heavy-duty applications especially are reliant on diesel engines for their high brake efficiency, power density, and robustness. Although engineering developments have advanced engines towards significantly fewer emissions and higher efficiency, the use of fossil-derived diesel as fuel sets a fundamental threshold in the achievable total net carbon reduction. Dimethyl ether can be produced from various renewable feedstocks and has a high chemical reactivity making it suitable for heavy-duty applications, namely compression ignition direct injection engines. Literature shows the successful use of DME fuels in diesel engines without significant hardware modifications.

As GHG and fuel economy regulations of light-duty vehicles have become more stringent, advanced emissions reduction technology has extensively penetrated the US light-duty vehicle fleet. This new technology includes not only advanced conventional engines and transmissions, but also greater adoption of electrified powertrains. In 2022, electrified vehicles – including mild hybrids, strong hybrids, plug-ins, and battery electric vehicles – made up nearly 17% of the US fleet and are on track to further increase their proportion in subsequent years. The Environmental Protection Agency (EPA) has previously used its Advanced Light-Duty Powertrain and Hybrid Analysis (ALPHA) full vehicle simulation tool to evaluate the greenhouse gas (GHG) emissions of light-duty vehicles. ALPHA contains a library of benchmarked powertrain components that can be matched to specific vehicles to explore GHG emissions performance.

A liquid-cooled plate is an important component for cooling batteries inside a battery package system. The structure of the liquid-cooling plate significantly affects the temperature conditions of power batteries and the energy consumption of the liquid-cooling system. However, there is a lack of precise knowledge regarding the specific factors that contribute to these impacts. In this study, the influence of structural parameters of flow channel on the heat dissipation performance is studied to solve above problems. A test bench for measuring battery pack cooling performances was built, and pressure drop of liquid-cooled plate and maximum temperature of battery were measured. A CFD model for liquid-cooled plate performance calculations was developed. Using the established model, pressure drop, and maximum temperature were calculated. The measured data are compared with the calculated date, which validate the proposed model.

The influence of the channels of a liquid-cooled plate on the heat dissipation performance of battery module is investigated in this paper. A topology optimization method for obtaining channel configurations of the liquid cooled plate is presented. Firstly, the battery pack cooling system test platform is built to test the flow resistance of the liquid-cooled plate under different flow rates and the maximum temperature and temperature difference of the battery under different working conditions. Secondly, the geometric model of the battery pack is established, and CFD software is used to simulate according to the test conditions. The test results validate the correctness of the model. Then, taking the average surface temperature of the liquid-cooled plate as the optimization objective, the topology optimization structure of the liquid-cooled plate is obtained by variable density method.