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Alternative fuels, such as natural and bio-gas, are attractive options for reducing greenhouse gas emissions from combustion engines. However, the naturally occurring variation in gas composition poses a challenge and may significantly impact engine performance. The gas composition affects fundamental fuel properties such as flame propagation speed and heat release rate. Deviations from the gas composition for which the engine was calibrated result in changes in the combustion phase, reducing engine efficiency and increasing fuel consumption and emissions. However, the efficiency loss can be limited by estimating the combustion phase and adapting the spark timing, which could be implemented favorably using a closed-loop control approach. In this paper, we evaluate the efficiency loss resulting from varying gas compositions and the benefits of using a closed-loop controller to adapt the spark timing to retain the nominal combustion phase.

Accurate estimation of battery state of health (SOH) has become indispensable in ensuring the predictive maintenance and safety of electric vehicles (EVs). While supervised machine learning excels in laboratory settings with adequate SOH labels, field-based SOH data collection for supervised learning is hindered by EVs' complex conditions and prohibitive data collection costs. To overcome this challenge, a battery SOH estimation method based on semi-supervised regression is proposed and validated using field data in this paper. Initially, the Ampere integral formula is employed to calculate SOH labels from charging data, and the error of labeled SOH is reduced by the open-circuit voltage correction strategy. The calculation error of the SOH label is confirmed to be less than 1.2%, as validated by the full-charge test of the battery packs.

The increasing need to reduce greenhouse gas emissions and shift away from fossil fuels has raised an interest for methanol. Methanol can be produced from renewable sources and can drastically lower soot emissions from compression ignition engines (CI). As a result, research and development efforts have intensified focusing on the use of methanol as a replacement for diesel in CI engines. The issue with methanol lies in the fact that methanol is challenging to ignite through compression alone, particularly at low-load and cold starts conditions. This challenge arises from methanol's high octane number, low heating value, and high heat of vaporization, all of which collectively demand a substantial amount of heat for methanol to ignite through compression.

The growing demand to lower greenhouse gas emissions and transition from fossil fuels, has put methanol in the spotlight. Methanol can be produced from renewable sources and has the property of burning almost soot-free in compression ignition (CI) engines. Consequently, there has been a notable increase in research and development activities directed towards exploring methanol as a viable substitute for diesel fuel in CI engines. The challenge with methanol lies in the fact that it is difficult to ignite through compression alone, particularly in low-load and cold start conditions. This difficulty arises from methanol's high octane number, relatively low heating value, and high heat of vaporization, collectively demanding a considerable amount of heat for methanol to ignite through compression. Previous studies have addressed the use of a pilot injection in conjunction with a larger main injection to lower the required intake air temperature for methanol to combust at low loads.

This paper investigates the tire-road interaction for tires equipped with two different solid rubber material definitions within a Finite Element Analysis virtual environment, ESI PAMCRASH. A Mixed Service Drive truck tire sized 315/80R22.5 is designed with two different solid rubber material definitions: a legacy hyperelastic solid Mooney-Rivlin material definition and an Ogden hyperelastic solid material definition. The popular Mooney-Rivlin is a material definition for solid rubber simulation that is not built with element elimination and is not easily applicable to thermal applications. The Ogden hyperelastic material definition for rubber simulations allows for element destruction. Therefore, it is of interest and more suited for designing a tire model with wear and thermal capabilities.

With the rise in demand, advanced steering control and electric vehicle technology are rapidly developing in modern times. Due to a controller's role as a backbone for the modern vehicle, its study has become increasingly crucial. This research proposes a novel 4th axle steering (4AS) feedforward controller that utilizes the first, second and fourth axle steering control for an 8x8 scaled electric combat vehicle. The vehicle is tested using the predefined path following. The novel 4AS controller is then compared to the Ackermann steering condition at different speeds. In the scaled vehicle used for this research, each wheel is independently driven by an in-wheel motor, while the steering is carried out by linear actuators. Individual eight-wheel steering control systems are designed and installed on the scaled vehicle to evaluate the driving performance from low speed to high speed. The 4AS steering method is implemented to improve the stability of the scaled vehicle at high speeds.

The present work discusses the potential benefits of using computational fluid dynamics (CFD) simulation and artificial intelligence (AI) in the design and optimization of hydrogen internal combustion engines (H2ICEs). A Machine Learning (ML) model is developed and applied to the CFD simulation data to identify optimal injection system parameters on the Sandia H2ICE Engine to improve the mixing. This approach can aid in developing predictive ML models to guide the design of future H2ICEs. For the current engine configuration, it is observed that hydrogen (H2) gas injection contributes mixing of H2 with air. If the injector parameters are optimized, mixture preparation is better and eventually combustion. A base CFD model is validated from the Sandia H2ICE engine data against Particle Image Velocimetry (PIV) data for velocity and Planar Laser Induced Fluorescence (PLIF) data for H2 mass fraction.

High Fidelity Communication has become a necessity in various sectors. Different wireless data transfer methods play a vital role in various far field and near-field communications. Wireless communication for transferring data through radio spectrum has been a continuous evolving trend, especially in Automotive Sector, with fleet monitoring, platooning and even connected vehicles. Some important parameters considered in selecting a wireless platform would be bandwidth, data transfer, speed and security. Some interesting advantages of communication over the visible spectrum has led to the evolution of Light Fidelity. Implementation of Visible Light Communication (VLC) in the automotive field might enable safer driving conditions through vehicle-to-vehicle (V2V) and vehicle to Infrastructure (V2I) communication with high data transmission rates and efficient-bandwidth usage. The principle of VLC is based on “line of sight” data transmission through modulation of the light source.

Throughout the world the efforts are being carried out to reduce the GHG emissions from transportation sector. As Volvo Group is a signatory of SBTi and having internal target of carbon neutrality by 2040, we have intensified & also diversified our R&D efforts to develop powertrains of the future having mix of conventional, various alternate fuels, electric etc. There will not be a unique solution or strategy suiting for all the markets in the world. Each market will have its own motivation & factors which OEMs need to consider while deciding the short term, midterm & long-term strategy for powertrain technology. Accordingly, OEMs must be ready with product mix suitable for all global markets. This paper will talk about the efforts taken and lessons learned during development of Hydrogen fuelled IC Engine. We used 8L Diesel IC engine as a base to convert it to Hydrogen powered IC engine, in a retrofit spirit, so that with minimum changes we could make the working prototype.

Excessive soot concentration in the lubricant promotes excessive wear on timing chains. The relationship between chain wear and soot concentration, morphology, and nanostructure, however, remains inconclusive. In this work, a chain wear test rig is used to motor a 1.3 L diesel engine following the speed profile of a Worldwide Harmonized Light Vehicle Test Cycle (WLTC). The lubricant oil was loaded with 3% carbon black of known morphology. The chain length is measured at regular intervals of 20 WLTC cycles (i.e. 10 hours) and the wear is expressed as a percentage of total elongation. Oil samples were collected and analysed with the same frequency as the chain measurements. Carbon black morphology and nanostructure were investigated using Dynamic Light Scattering (DLS) and Transmission Electron Microscopy (TEM).

Using renewable fuels is a reliable approach for decarbonization of combustion engines. iso-Butanol and n-butanol are known as longer chain alcohols and have the potential of being used as gasoline substitute or a renewable fraction of gasoline. The combustion behavior of renewable fuels in modern combustion engines and advanced combustion concepts is not well understood yet. Low-temperature combustion (LTC) is a concept that is a basis for some of the low emissions-high efficiency combustion technologies. Fuel ɸ-sensitivity is known as a key factor to be considered for tailoring fuels for these engines. The Lund ɸ-sensitivity method is an empirical test method for evaluation of the ɸ-sensitivity of liquid fuels and evaluate fuel behavior in thermal. iso-Butanol and n-butanol are two alcohols which like other alcohol exhibit nonlinear behavior when blended with (surrogate) gasoline in terms of RON and MON.

The worldwide adoption of renewable energy mandates, together with the widespread utilization of biofuels has created a sharp increase in the production of biodiesel (fatty acid alkyl esters). As a consequence, the production of glycerol, the main by-product of the transesterification of fatty acids, has increased accordingly, which has led to an oversupply of that compound on the markets. Therefore, in order to increase the sustainability of the biodiesel industry, alternative uses for glycerol need to be explored and the production of fuel additives is a good example of the so-called glycerol valorization. The goal of this study is therefore to evaluate the suitability of a number of glycerol-derived compounds as diesel fuel additives. Moreover, this work concerns the assessment of low-concentration blends of those glycerol derivatives with diesel fuel, which are more likely to conform to the existing fuel standards and be used in unmodified engines.

This study explores the potential benefits of combining a wave-shaped piston geometry with post injection strategy in diesel engines. The wave piston design features evenly spaced protrusions around the piston bowl, which improve fuel-air mixing and combustion efficiency. The 'waves' direct the flames towards the bowl center, recirculating them and utilizing the momentum in the flame jets for more complete combustion. Post injection strategy, which involves a short injection after the main injection, is commonly used to reduce emissions and improve fuel efficiency. By combining post injections with the wave piston design, additional fuel injection can increase the momentum utilized by the flame jets, potentially further improving combustion efficiency. To understand the effects and potential of the wave piston design with post injection strategy, a single-cylinder heavy-duty compression-ignition optical engine with a quartz piston is used.

This paper investigates the impact of tread design on the tire-terrain interaction of two similar-sized truck tires with distinctly different tread designs running over various terrains and operating conditions using advanced computation techniques. The two truck tires used in the research are off-road tires sized 315/80R22.5 wide which were designed through Finite Element Analysis (FEA). The truck tire models were validated in static and dynamic domains using several simulation tests and measured data. The terrain includes a flooded surface and a snowed surface which were modelled using Smoothed-Particle Hydrodynamics (SPH) technique and calibrated using pressure-sinkage and direct shear tests. Both truck tire models were subjected to rolling resistance and cornering tests over the various flooded surface and snowed surface terrain conditions on the PAM-CRASH software.

This article presents an autonomous steering control scheme for articulated heavy vehicles (AHVs). Despite economic and environmental benefits in freight transportation, lateral stability is always a concern for AHVs in high-speed highway operations due to their multi-unit vehicle structures, and high centers of gravity (CGs). In addition, North American harsh winter weather makes the lateral stability even more challenging. AHVs often experience amplified lateral motions of trailing vehicle units in high-speed evasive maneuvers. AHVs represent a 7.5 times higher risk than passenger cars in highway operation. Human driver errors cause about 94% of traffic collisions. However, little attention has been paid to autonomous steering control of AHVs.

Heavy-duty vehicles are primarily powered by diesel fuel, emitting CO2 emissions regardless of the exhaust after-treatment system. Contrastingly, a hydrogen engine has the potential to decarbonize the transportation sector as hydrogen is a carbon free, renewable fuel. In this study, a multi-physics 1D simulation tool (GT-Power) is used to model the gas exchange process and performance prediction of a two-stroke hydrogen engine. The aim is to establish a maximum torque-level for a four-stroke hydrogen engine and then utilize different methods for two-stroke modeling to achieve similar torque by optimizing the gas exchange process. A camless engine is used as base, enabling the flexibility to utilize approximately square valve lift profiles. The preliminary step is the GT-Power model validation, which has been done using diesel and hydrogen engines (single-cylinder heavy-duty) experiments at different operating points (871 rpm, 1200 rpm, 1259 rpm, and 1508 rpm).

A modern diesel engine is a reliable and efficient mean of producing power. A way to reduce harmful exhaust and greenhouse gas (GHG) emissions and secure the sources of energy is to develop technology for an efficient diesel engine operation independent of fossil fuels. Renewable diesel fuels are compatible with diesel engines without any major modifications. Rapeseed oil methyl esters (RME) and other fatty acid methyl esters (FAME) are commonly used in low level blends with diesel. Lately, hydrotreated vegetable oil (HVO) produced from vegetable oil and waste fat has found its way into the automotive market, being approved for use in diesel engines by several leading vehicle manufacturers, either in its pure form or in a mixture with the fossil diesel to improve the overall environmental footprint. There is a lack of data on how renewable fuels change the semi-volatile organic fraction of exhaust emissions.

Increasingly stringent pollutant and CO2 emission standards require the car manufacturers to investigate innovative solutions to further improve the fuel economy and environmental impact of their fleets. Nowadays, NOx emissions standards are stringent for spark-ignition (SI) internal combustion engines (ICEs) and many techniques are investigated to limit these emissions. Among these, an extremely lean combustion has a large potential to simultaneously reduce the NOx raw emissions and the fuel consumption of SI ICEs. Engines with pre-chamber ignition system are promising solutions for realizing a high air-fuel ratio which is both ignitable and with an adequate combustion speed. In this work, the combustion characteristics of an active pre-chamber system are experimentally investigated using a single-cylinder research engine. The engine under exam is a large bore heavy-duty unit with an active pre-chamber fuelled with compressed natural gas.

The physical characteristics of Mars's soil have an impact on how easily a spacecraft can land and navigate the planet's surface. On the surface of Mars, wheeled robots known as "rovers" were planted to carry out scientific investigations on the planet's historical temperature, surface geology, and possibilities for past or current life. The challenges of guiding mobile robots across terrain that is sloping, rocky, and deformable have brought to light the significance of creating precise simulation models of the tire and mars soil interaction. In this paper, current efforts to create a terramechanics-based model of rover movement using a Non-Pneumatic (NP) tire on planetary surfaces are discussed. Since no rocks or soils have been brought back to Earth from Mars, Martian simulants are frequently used for testing rovers and other devices for Mars terrain research.

Due to traffic congestion and environmental pollution, connected automated vehicle (CAV) technologies based on vehicle-to-vehicle (V2V) and vehicle-to-infrastructure communication (V2I) have gained increasing attention from both academia and industry. Connected hybrid electric vehicles (CHEVs) offer great opportunities to reduce vehicular operating costs and emissions. However, in complex traffic scenarios, high-quality real-time energy management of CHEVs remains a technical challenge. To address the challenge, this paper proposes a hierarchical eco-driving strategy that consists of speed planning and energy management layers. At the upper layer, by leveraging the real-time traffic data provided by vehicle-to-everything (V2X) communication, dynamic traffic constraints are predicted by the traffic flow predictor developed based on the Hankel dynamic mode decomposition algorithm (H-DMD).