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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.

A high-power photovoltaic (PV) system for an electric vehicle was fabricated. The total rated power of the PV panels was 1150 W. A demonstration test was conducted for a year. The test data showed that the prototype PV system was able to generate energy equivalent to approximately 7,100 km/year in driving distance. It was also found that if the vehicle is used for commuting about 10 km one way, it is mostly not necessary to recharge the vehicle from the grid throughout the year. In addition, the system was able to maintain maximum power point tracking (MPPT) control during driving even when the solar radiation changed frequently.

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.

There are two primary technical issues in the application of position sensorless control to generators for 100% electric-drive hybrid vehicles. The first is the risk of losing control when position sensorless estimation methods are changed in accordance with the generator speed, while. The second is the reduction in the maximum torque if the rate of change in the generator speed is extremely large in a relatively low-rotation-speed area. This study proposes countermeasures for each issue and their effects examines them via simulations and experiments.

In electrified automobiles, wind noise significantly contributes to the overall noise inside the cabin. In particular, underbody airflow is a dominant noise source at low frequencies (less than 500 Hz). However, the wind noise transmission mechanism through a battery electric vehicle (BEV) underbody is complex because the BEV has a battery under the floor panel. Although various types of underbody structures exist for BEVs, in this study, the focus was on an underbody structure with two surfaces as inputs of wind noise sources: the outer surface exposed to the external underbody flow, such as undercover and suspension, and the floor panel, located above the undercover and battery. In this study, aero-vibro-acoustic simulations were performed to clarify the transmission mechanism of the BEV underbody wind noise. The external flow and acoustic fields were simulated using computational fluid dynamics.

The size and weight of the traction inverter needs to be reduced to ensure a sufficient cruising range of an electric vehicle. To this end, one approach involves changing materials of the inverter case from aluminum to resin. However, the resin in use of inverter case causes technical issues in terms of collision performance, electromagnetic compatibility (EMC), and cooling performance because of the difference in the material properties between the resin and the conventionally used aluminum. By solving the abovementioned issues, a resin water jacket case (hereinafter, resin water jacket) was successfully adopted with inverters designed for next-generation electric powertrain in mass production models for the first time. The resin-based structure had advantages to reduce the weight of the inverter case by ~35% and decrease the number of parts to ~3/5, compared to that for the conventional cases.

The adoption of electric vehicles (EVs) has been announced worldwide with the aim of reducing CO2 emissions. However, a significant increase in electricity demand by EVs might impact the stable operation of the existing power grid. Meanwhile, EV charging is acceptable to most users if it is completed by the time of the next driving event. From the viewpoint of power grid operators, flexibility for shifting the timing of EV charging would be advantageous, including making effective use of renewable energy. In this work, an EV model and simulation tool were developed to make clear how the total charging demand of all EVs in use will be influenced by future EV specifications (e.g., charge power) and installation of charging infrastructure. Among the most influential factors, EV charging behavior according to use cases and regional characteristics were statistically analyzed based on the real-world usage data of over 14, 000 EVs and incorporated in the simulation tool.

It is well known that the wheels and tires account for approximately 25% of the overall aerodynamic drag of a vehicle. This is because the contribution of the tires to aerodynamic drag stems from not only aerodynamic drag itself directly caused by exposure to the main flow (tire CD), but also from aerodynamic drag indirectly caused by the interference between tire wakes and the upper body flow (body CD). In the literature, as far as the authors are aware, there have been no reports that have included the following all four aspects at once: (1) CD sensitivity to detailed tire shape factors; (2) CD sensitivity differences due to different vehicle body types; (3) CD sensitivity for each aerodynamic drag component, i.e., tire CD and body CD; (4) Flow structure and mechanism contributing to each aerodynamic drag component. The purpose of this study was to clarify CD sensitivity to tire shape factors for tire CD and body CD considering two different vehicle body types, sedan and SUV.

In order to improve the accuracy of the coil temperature prediction, detailed fundamental experiments have been conducted on thermal resistances that are caused by the void air gap and contact surfaces. The thermal resistance of the coil around the air gap can be calculated by an air gap distance and air heat conductivity. Contact surface thermal resistance between the core and the housing was constant regardless of the press-fitting state in this experiment. Prediction accuracy of the coil temperature is improved by including the heat resistance characteristics that is obtained by the basic experiment to conjugate heat transfer analysis model.

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.

A new variable compression turbo (VC-Turbo) engine, which has a multi-link system for controlling the compression ratio from 8:1 to 14:1, requires high axial force for fastening the multi-links because of high input loads and the downsizing requirement. Therefore, it was necessary to develop a 1.6-GPa tensile strength bolt with plastic region tightening. One of the biggest technical concerns is delayed fracture. In this study, quenched and tempered alloy steels were chosen for the 1.6-GPa tensile strength bolt.

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.

Wheels play an important role in determining the aerodynamic drag of passenger vehicles. This is because the contribution of wheels to aerodynamic drag comes from not only the wheels themselves, but also from the interference effect between wheel wakes and the base wake. As far as the authors are aware, there have been no reports about aerodynamic drag sensitivity to wheel shape factors for different vehicle types and different exterior body shapes. The purpose of this study was to clarify CD sensitivity to wheel shape factors for a sedan and an SUV, including different rear fender shapes. Many different wheel configurations were investigated in terms of the CD, base pressure and flow fields in wind tunnel tests. Multiple regression analyses were conducted to clarify CD sensitivity to each wheel shape factor based on the test data. This study revealed high CD sensitivity factors for both the sedan and SUV.

An electric vehicle (EV) has less powertrain energy loss than an internal combustion engine vehicle (ICE), so its aerodynamic accounts have a larger portion of drag contribution of the total energy loss. This means that EV aerodynamic performance has a larger impact on the all-electric range (AER). Therefore, the target set for the aerodynamics development for a new EV hatchback was to improving AER for the customer’s benefit. To achieve lower aerodynamic drag than the previous model’s good aerodynamic performance, an ideal airflow wake structure was initially defined for the new EV hatchback that has a flat underbody with no exhaust system. Several important parameters were specified and proper numerical values for the ideal airflow were defined for them. As a result, the new EV hatchback achieves a 4% reduction in drag coefficient (CD) from the previous model.

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.

There are strong demands for vehicle weight reductions so as to improve fuel economy. At the same time, it is also necessary to ensure crash safety. One effective measure for accomplishing such both requirements conflicting each other is to apply advanced high strength steel (AHSS) of 780 MPa grade or higher to the vehicle body. On the other hand, higher strength steels generally tend to display lower elongation causing formability deterioration. Nissan Motor Corporation have jointly developed with steel manufacturers a new 980 MPa grade AHSS with high formability with the aim of substituting it for the currently used 590 MPa grade high-tensile steel. Several application technologies have been developed through the verifications such as formability, resistance spot weldability, crashworthiness, and delayed fracture.

In open-grille vehicle aerodynamics simulation using computational fluid dynamics, in addition to basic flow characteristics, such as turbulent flow with a Reynolds number of several million on the bluff body, it is important to accurately estimate the cooling air flow introduced from the front opening. It is therefore necessary to reproduce the detailed geometry of the entire vehicle including the engine bay as precisely as possible. However, there is a problem of generating a good-quality calculation grid with a small workload. It usually takes several days to a week for the pretreatment process to make the geometry data ‘clean’ or ‘watertight’. The authors proposed a computational method for complex geometries with a hierarchical Cartesian grid and a topology-independent immersed boundary method with dummy cells that discretize the geometry on a cell-by-cell basis and can set an imaginary point arbitrarily.

During the last decade, fuel economy mandates (CAFE regulations) have driven engine downsizing and down-speeding trends. More recently, downsized turbos are percolating down to heavier SUVs and trucks. Larger/heavier vehicles require high torque engines to provide attractive dynamic performance. While higher torque requirements can be satisfied with new innovations like the variable compression engine, larger and more upscale vehicles also need to deliver higher quietness requirements. For this, the vibration control system for combustion induced forces with high torque engines become very important. To address both dynamic performance and quietness requirements, active engine mounts have been previously adopted, however challenges for light-weighting, downsizing, and costs have still persisted.

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.

This paper describes a study of drag reduction devices for production pick-up trucks with a body-on-frame structure using full-scale wind tunnel testing and Computational Fluid Dynamics (CFD) simulations. First, the flow structure around a pick-up truck was investigated and studied, focusing in particular on the flow structure between the cabin and tailgate. It was found that the flow structure around the tailgate was closely related to aerodynamic drag. A low drag flow structure was found by flow analysis, and the separation angle at the roof end was identified as being important to achieve the flow structure. While proceeding with the development of a new production model, a technical issue of the flow structure involving sensitivity to the vehicle velocity was identified in connection with optimization of the roof end shape. (1)A tailgate spoiler was examined for solving this issue.