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Accurately predicting real-world vehicle energy consumption is essential for optimizing vehicle designs, enhancing energy efficiency, and developing effective energy management strategies. This paper presents a data-driven approach that utilizes machine learning techniques and a comprehensive dataset of vehicle parameters and environmental factors to create precise energy consumption prediction models. The methodology involves recording real-world vehicle data using data loggers to extract information from the CAN bus systems for ICE and hybrid electric, as well as hydrogen and battery fuel cell vehicles. Data cleaning and cycle-based analysis are employed to process the dataset for accurate energy consumption prediction. This includes cycle detection and analysis using methods from statistics and signal processing, and then pattern recognition based on these metrics.

Internal combustion (IC) engines still power most of the vehicles on road and will likely to remain so in the near future, especially for heavy duty applications in which electrification is typically more challenging. Therefore, continued improvements on IC engines in terms of efficiency and longevity are necessary for a more sustainable transportation sector. Two important design objectives for heavy duty engines with wet liners are to reduce friction loss and to lower the risks of cavitation damages, both of which can be greatly influenced by the piston-liner clearance and the design of the piston skirt. However, engine design optimization is difficult due to the nonlinear interactions between the key design variables and the design objectives, as well as the multi-physics and multi-scale nature of the mechanisms that are relevant to the design objectives.

Lubricating oil consumption (LOC) is a direct source of hydrocarbon and particulate emissions from internal combustion engines. LOC also inhibits the lifetime of exhaust aftertreatment system components, preventing their ability to effectively filter out other harmful emissions. Due to its influence on piston ring- bore conformability, bore distortion is arguably the most critical parameter for engine designers to consider in prevention of LOC. Bore distortion also has a significant influence on the contact forces between the piston ring and cylinder wall, which determine the wear rate of the ring and cylinder wall and can cause durability issues. Two drivers of bore distortion: thermal expansion and head bolt stresses, are routinely considered in conformability and contact analyses. Separately, bore distortion/vibration due to piston impact and combustion/cylinder pressures has been previously analyzed in wet liner engines for coolant cavitation and noise considerations.

In an engine system, the piston pin is subjected to high loading and severe lubrication conditions, and pin seizures still occur during new engine development. A better understanding of the lubricating oil behavior and the dynamics of the piston pin could lead to cost- effective solutions to mitigate these problems. However, research in this area is still limited due to the complexity of the lubrication and the pin dynamics. In this work, a numerical model that considers structure deformation and oil cavitation was developed to investigate the lubrication and dynamics of the piston pin. The model combines multi-body dynamics and elasto-hydrodynamic lubrication. A routine was established for generating and processing compliance matrices and further optimized to reduce computation time and improve the convergence of the equations. A simple built-in wear model was used to modify the pin bore and small end profiles based on the asperity contact pressures.

The increasing demand for environmentally friendly and fuel-efficient transportation and power generation requires further optimization and minimization of friction power losses. With up to 50% of the overall friction, the piston cylinder unit (PCU) shows most potential within the internal combustion engine (ICE) to increase mechanical efficiency. Calculating friction of internal combustion engines, especially the friction contribution from piston rings and skirt, requires detailed knowledge of the dynamics and lubrication regime of the components being in contact. Part I of this research presents a successful match of simulated and measured piston inter-ring pressures at numerous operation points [1] and constitutes the starting point for the comparison of simulated and measured piston group friction forces as presented in this research.

As the piston pin works under significant mechanical load, it is susceptible to wear, seizure, and structural failure, especially in heavy duty internal combustion engines. It has been found that the friction loss associated with the pin is comparable to that of the piston, and can be reduced when the interface geometry is properly modified. However, the mechanism that leads to such friction reduction, as well as the approaches towards further improvement, remain unknown. This work develops a piston pin lubrication model capable of simulating the interaction between the pin, the piston, and the connecting rod. The model integrates dynamics, solid contact, oil transport, and lubrication theory, and applies an efficient numerical scheme with second order accuracy to solve the highly stiff equations. As a first approach, the current model assumes every component to be rigid.

In internal combustion engines, the majority of the friction loss associated with the piston takes place on the thrust side in early expansion stroke. Research has shown that the Friction Mean Effective Pressure (FMEP) of the engine can be reduced if proper modifications to the piston skirt, which is traditionally barrel-shaped, are made. In this research, an existing model was applied for the first time to study the effects of different oil supply strategies for the piston assembly. The model is capable of tracking lubricating oil with the consideration of oil film separation from full film to partial film. It is then used to analyze how the optimized piston skirt profile investigated in a previous study reduces friction.

With the recent advancement in sensing and controller technologies architecture design of an autonomous driving system becomes an important issue. Researchers have been developing different sensors and data processing technologies to solve the issues associated with fast processing, diverse weather, reliability, long distance recognition performance, etc. Necessary considerations of diverse traffic situations and safety factors of autonomous driving have also increased the complexity of embedded software as well as architecture of autonomous driving. In these circumstances, there are almost countless numbers of possible architecture designs. However, these design considerations have significant impacts on cost, controllability, and system reliability. Thus, it is crucial for the designers to make a challenging and critical design decision under several uncertainties during the conceptual design phase.

This paper describes a post-race analysis of team KOMMIT EVT’s electric motorcycle data collected during the 2016 Pikes Peak International Hill Climb (PPIHC). The motorcycle consumed approximately 4 kWh of battery energy with an average and maximum speed of 107 km/h and 149 km/h, respectively. It was the second fastest electric motorcycle with a finishing time of 11:10.480. Data was logged of the motorcycle’s speed, acceleration, motor speed, power, currents, voltages, temperatures, throttle position, GPS position, rider’s heart rate and the ambient environment (air temperature, pressure and humidity). The data was used to understand the following factors that may have prevented a faster time: physical fitness of the rider, thermal limits of the motor and controller, available battery energy and the sprocket ratio between the motor and rear wheel.

The distribution of lubricating oil plays a critical role in determining the friction between piston skirt and cylinder liner, which is one of the major contributors to the total friction loss in internal combustion engines. In this work, based upon the experimental observation an existing model for the piston secondary motion and skirt lubrication was improved with a physics-based model describing the oil film separation from full film to partial film. Then the model was applied to a modern turbo-charged SI engine. The piston-skirt FMEP predicted by the model decreased with larger installation clearance, which was also observed from the measurements using IMEP method at the rated. It was found that the main period of the cycle exhibiting friction reduction is in the expansion stroke when the skirt only contacts the thrust side for all tested installation clearances.

Higher compression ratio and turbocharging, with engine downsizing can enable significant gains in fuel economy but require engine operating conditions that cause engine knock under high load. Engine knock can be avoided by supplying higher-octane fuel under such high load conditions. This study builds on previous MIT papers investigating Octane-On-Demand (OOD) to enable a higher efficiency, higher-boost higher compression-ratio engine. The high-octane fuel for OOD can be obtained through On-Board-Separation (OBS) of alcohol blended gasoline. Fuel from the primary fuel tank filled with commercially available gasoline that contains 10% by volume ethanol (E10) is separated by an organic membrane pervaporation process that produces a 30 to 90% ethanol fuel blend for use when high octane is needed. In addition to previous work, this paper combines modeling of the OBS system with passenger car and medium-duty truck fuel consumption and octane requirements for various driving cycles.

In internal combustion engines, a portion of liquid fuel spray may directly land on the liner and mix with oil (lubricant), forming a fuel-oil film (~10μm) that is much thicker than the original oil film (~0.1μm). When the piston retracts in the compression stroke, the fuel-oil mixture may have not been fully vaporized and can be scraped by the top ring into the 1st land crevice and eventually enter the combustion chamber in the format of droplets. Studies have shown that this mechanism is possibly a leading cause for low-speed pre-ignition (LSPI) as the droplets contain oil that has a much lower self-ignition temperature than pure fuel. In this interest, this work aims to study the oil-fuel interactions on the liner during an engine cycle, addressing molecular diffusion (in the liquid film) and vaporization (at the liquid-gas interface) to quantify the amount of fuel and oil that are subject to scraping by the top ring, thereby exploring their implications on LSPI and friction.

Ground impact caused by road debris can result in very severe fire accident of Electric Vehicles (EV). In order to study the ground impact accidents, a Finite Element model of the battery pack structure is carefully set up according to the practical designs of EVs. Based on this model, the sequence of the deformation process is studied, and the contribution of each component is clarified. Subsequently, four designs, including three enhanced shield plates and one enhanced housing box, are investigated. Results show that the BRAS (Blast Resistant Adaptive Sandwich) shield plate is the most effective structure to decrease the deformation of the battery cells. Compared with the baseline case, which adopts a 6.35-mm-thick aluminum sheet as the shield plate, the BRAS can reduce the shortening of cells by more than 50%. Another type of sandwich structure, the NavTruss, can also improve the safety of battery pack, but not as effectively as the BRAS.

A new ring pack model has been developed based on the curved beam finite element method. This paper describes the first part of this model: simulating gas pressure in different regions above piston skirt and ring dynamic behavior of two compression rings and a twin-land oil control ring. The model allows separate grid divisions to resolve ring structure dynamics, local force/pressure generation, and gas pressure distribution. Doing so enables the model to capture both global and local processes at their proper length scales. The effects of bore distortion, piston secondary motion, and groove distortion are considered. Gas flows, gas pressure distribution in the ring pack, and ring structural dynamics are coupled with ring-groove and ring-liner interactions, and an implicit scheme is employed to ensure numerical stability. The model is applied to a passenger car engine to demonstrate its ability to predict global and local effects on ring dynamics and oil transport.

Electric vehicles have a strong potential to reduce a continued dependence on fossil fuels and help the environment by reducing pollution. Despite the desirable advantage, the introduction of electrified vehicles into the market place continues to be a challenge due to cost, safety, and life of the batteries. General Motors continues to bring vehicles to market with varying level of hybrid functionality. Since the introduction of Li-ion batteries by Sony Corporation in 1991 for the consumer market, significant progress has been made over the past 25 years. Due to market pull for consumer electronic products, power and energy densities have significantly increased, while costs have dropped. As a result, Li-ion batteries have become the technology of choice for automotive applications considering space and mass is very critical for the vehicles.

A new ring pack model has been developed based on the curved beam finite element method. This paper describes the second part of this model: simulating oil transport around the ring pack system (two compression rings and one twin-land oil control ring (TLOCR)) through the ring-liner interfaces by solving the oil film thickness on the liner. The ring dynamics model in Part 1 calculates the inter-ring gas pressure and the ring dynamic twist which are used in the ring-liner lubrication model as boundary conditions. Therefore, only in-plane conformability is calculated to obtain the oil film thickness on the liner. Both global process, namely, the structural response of the rings to bore distortion and piston tilt, and local processes, namely, bridging and oil-lube interaction, are considered. The model was applied to a passenger car engine.

The first 3 cycles in the cold crank-start process at 20°C are studied in a GDI engine. The focus is on the dependence of the HC and PM/PN emissions of each cycle on the injection strategy and combustion phasing of the current and previous cycles. The PM/PN emissions per cycle decrease by more than an order of magnitude as the crank-start progresses from the 1st to the 3rd cycle, while the HC emissions stay relatively constant. The wall heat transfer, as controlled by the combustion phasing, during the previous cycles has a more significant influence on the mixture formation process for the current cycle than the amount of residual fuel. The results show that the rise in HC emissions caused by the injection spray interacting with the intake valves and piston crown is reduced as the cranking process progresses. Combustion phasing retard significantly reduces the PM emission. The HC emissions, however, are relatively not sensitive to combustion phasing in the range of interest.

The piston skirt is an important contributor of friction in the piston assembly. This paper discusses friction contributions from various aspects of the piston skirt. A brief study of piston skirt patterns is presented, with little gains being made by patterning the piston skirt coating. Next the roughness of the piston skirt coating is analyzed, and results show that reducing piston skirt roughness can have positive effects on friction reduction. Finally, an introductory study into the profile of the piston skirt is presented, with the outcome being that friction reduction is possible by optimizing the skirt profile.

The piston’s skirt shape is a key design parameter since it critically influences lateral displacement, tilting movement, oil transport and consequently engine performances. This study proposes an alternative skirt profile that aims to reduce frictional losses between the piston and cylinder liner. Qualitatively, the proposed profile, aims to reduce solid-to-solid contact friction by increasing the total hydrodynamic forces generated on the skirt to balance side forces, and to prevent both sides of the skirt to interact with the liner simultaneously. The new skirt’s profile has been first studied and optimized using a piston secondary motion model and then prototyped and tested on a floating liner test bench, showing a 12% average reduction in total piston FMEP.

Understanding oil transport mechanisms is critical to developing better tools for oil consumption and piston skirt lubrication [1]. Our existing Two-Dimensional Laser Induced Fluorescence (2DLIF) system with an acquisition rate of 1 frame every one or two cycles was proven to be effective to display oil accumulation patterns and their evolution over many cycles in the piston ring pack system [2,3,4]. Yet, the existing system is unable to resolve instantaneous oil flow patterns in the piston-liner interface. In this work, a high-speed LIF system was developed. After a number of iterations the finalized high speed LIF system includes a 23 W, 100 kHz, 532 nm laser and a high speed camera capable of 100,000 FPS at 384 × 264 pixel resolution. After each component was selected, optimization of the quality of images taken from the system began.