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The environment is one of the most important issues currently facing the world and the automobile industry is required to respond with eco-cars. To meet this requirement, the hybrid vehicle is one of the most optimal solutions. The hybrid system automatically stops engine idling (idling stop), or stops the engine during deceleration to recover energy. The engine stop however creates a problem concerning the vehicle's climate control system. Because the conventional climate control system incorporates a compressor driven by engine belt, there is almost no cooling performance while the engine is stopped. Until now, when a driver needed more cooling comfort the engine has been switched back on as a compromise measure. To realize cabin comfort that is consistent with fuel saving, a 2-way driven compressor has been developed that can be driven both by engine belt while the engine is running and by electric motor when the engine is stopped.

In the 42V Mild Hybrid System introduced into market by Toyota for the first time in the world, the crankshaft using belt(s) drives the motor/generator (MG). The set-up employs an inverter unit to control the MG electronically. This paper describes the system configuration, operations, characteristic features and development results of the new power control system. The focus is on the MG, the inverter-for-MG-control and energy regeneration, as well as DC/DC converter for the power supply to the 14V devices.

The significance and the number of vehicle safety features enabled via connectivity continue to increase. OnStar, with its automatic airbag notification, was one of the first vehicle safety features that demonstrate the enhanced safety benefits of connectivity. Vehicle connectivity benefits have grown to include remote software updates, data analytics to aid with preventative maintenance and even to theft prevention and recovery. All of these services require available and reliable connectivity. However, except for the airbag notification, none have strict latency requirements. For example, software updates can generally be postponed till reliable connectivity is available. Data required for prognostic use cases can be stored and transmitted at a later time. A new set of use cases are emerging that do demand continuous, reliable and low latency connectivity. For example, remote control of autonomous vehicles may be required in unique situations.

Inerters have become a hot topic in recent years, especially in vehicle, train, and building suspension systems. The performance of a passive inerter and a semi-active inerter was analyzed and compared with each other and it showed that the semi-active inerter has much better performance than the passive inerter, especially with the Hybrid control method. Eight different layouts of suspensions were analyzed with a quarter car model in this paper. The adaptation of dimensionless parameters was considered for a semi-active suspension and the semi-active inerters. The performance of the semi-active inerter suspensions with different layouts was compared with a semi-active suspension with a conventional parallel spring-damper arrangement. It shows a semi-active suspension, with more simple configuration and lower cost, has similar or better compromise between ride and handling than a semi-active inerter with the Hybrid control.

This paper presents a custom integrated circuit (IC) on which circuit functions necessary for “Active Hydraulic Brake (AHB) system” are integrated, and its key component, “Current-to-Digital Converter” for solenoid current measurement. The AHB system, which realizes a seamless brake feeling for Antilock Brake System (ABS) and Regenerative Brake Cooperative Control of Hybrid Vehicle, and the custom IC are installed in the 4th-generation Prius released in 2015. In the AHB system, as linear solenoid valves are used for hydraulic brake pressure control, high-resolution and high-speed sensing of solenoid current with ripple components due to pulse width modulation (PWM) is one of the key technologies. The proposed current-to-digital converter directly samples the drain-source voltage of the sensing DMOS (double-diffused MOSFET) with an analog-to-digital (A/D) converter (ADC) on the IC, and digitizes it.

Future Automotive Systems Technology Simulator (FASTSim) is a free and open-source tool developed by National Renewable Energy Lab (NREL). Among the attractive capabilities of the FASTSim is that it can perform computationally efficient fuel economy simulations of automotive vehicles with reasonable accuracy for standard or arbitrary drive cycles. The modeling capability includes vehicles with various types of powertrains such as: conventional vehicles (CVs), hybrid-electric vehicles (HEVs), plugin hybrid electric vehicles (PHEVs) and battery-only electric vehicles (BEVs). The public version of FASTSim available from NREL is implemented in Excel, which achieves the goal of good accessibility to a broad audience, but has some limitations, including: i) bottleneck in computations when importing arbitrary drive cycles, ii) slower computations in general than other scripting or programming languages, and iii) less portable to integration with other applications and/or other platforms.

This study pertains to motion control algorithms using statistical calculations based on relative displacement measurements, in particular where the rattle space is strictly limited by fixed end-stops and a load leveling system that allows for roll to go undetected by the sensors. One such application is the cab suspension of semi trucks that use widely-spaced springs and dampers and a load leveling system that is placed between the suspensions, near the center line of the cab. In such systems it is possible for the suspension on the two sides of the vehicle to settle at different ride heights due to uneven loading or the crown of the road. This paper will compare the use of two moving average signals (one positive and one negative) to the use of one root mean square (RMS) signal, all calculated based on the relative displacement measurement.

Driver Assistance and Autonomous Driving features are becoming nearly ubiquitous in new vehicles. The intent of the Driver Assistant features is to assist the driver in making safer decisions. The intent of Autonomous Driving features is to execute vehicle maneuvers, without human intervention, in a safe manner. The overall goal of Driver Assistance and Autonomous Driving features is to reduce accidents, injuries, and deaths with a comforting driving experience. However, different drivers can react differently to advanced automated driving technology. It is therefore important to consider and improve the adaptability of these advances based on driver behavior. In this paper, a human-centric approach is adopted to provide an enriching driving experience. We perform data analysis of the naturalistic behavior of drivers when performing lane change maneuvers by extracting features from extensive Second Strategic Highway Research Program (SHRP2) data of over 5,400,000 data files.

The objective of this work is to provide a relatively simple battery energy storage and loss model that can be used for technology screening and design/sizing studies of hybrid electric vehicle powertrains. The model dynamic input requires only power demand from the battery terminals (either charging or discharging), and outputs internal battery losses, state-of-charge (SOC), and pack temperature. Measured data from a vehicle validates the model, which achieves reasonable accuracy for current levels up to 100 amps for the size battery tested. At higher current levels, the model tends to report a higher current than what is needed to create the same power level shown through the measured data. Therefore, this battery model is suitable for evaluating hybrid vehicle technology and energy use for part load drive cycles.

This paper studies the effect of different longitudinal load conditions, roundabout cross-sectional geometry, and different semi-truck pneumatic suspension systems on roll stability in roundabouts, which have become more and more popular in urban settings. Roundabouts are commonly designed in their size and form to accommodate articulated heavy vehicles (AHVs) by evaluating such affects as off-tracking. However, the effect of the roadway geometry in roundabouts on the roll dynamics of semi-tractors and trailers are equally important, along with their entry and exit configuration. , Because the effect of the roundabout on the dynamics of trucks is further removed from the immediate issues considered by roadway planner, at times they are not given as much consideration as other roadway design factors.

Quietness is one of the most important characteristics for Hybrid Electric Vehicle quality. Reduction of the rattle noise caused by the torque fluctuation of an internal combustion engine can contribute to get a customer satisfaction. Toyota Hybrid System(THS) also has same requirement. Especially, the rattle noise during idling may happen discontinuously despite of periodical engine combustion excitation. It is necessary to study the mechanism and reduce the rattle noise. At lower engine torque range, decreasing the torsional damper’s stiffness can improve this condition as the manual transaxle done. However, the rattle noise can occur easily in conditions of relatively large torque spike inputs to the torsional system, such as the engine start/stop function of THS using the motor/generator in the transaxle.

Plugin hybrid electric vehicles (PHEVs) have several attractive features in terms of reduction of greenhouse gas (GHG) emissions. Compared to conventional vehicles (CVs) that only have an internal combustion engine (ICE), PHEVs have better energy efficiency like regular hybrids (HEVs), allow for electrifying an appreciable portion of traveled miles, and have no range anxiety issues like battery-only electric vehicles (BEVs). However, in terms of criteria emissions (e.g., NOx, NMOG, HC), it is unclear if PHEVs are any better than HEVs or CVs. Unlike GHG emissions, criteria emissions are not continuously emitted in proportional quantities to fossil fuel consumption. Rather, the amount and type of criteria emissions is a rather complex function of many factors, including type of fuel, ICE temperature, speed and torque, catalyst temperature, as well as the ICE controls (e.g., fuel-to-air ratio, valve and ignition timing).

Traffic accidents in the United States were analyzed using FARS and NASS data. When classified according to vehicle body type and collision type, fatalities were most common in the case of (1) passenger car to passenger car frontal impacts, (2) passenger car to passenger car side impacts, (3) passenger car to LTV side impacts, (4) passenger car to truck frontal impacts, and (5) passenger car to LTV frontal impacts. Among these collisions, it was clearly confirmed that the occupants of a passenger car have a strong tendency to suffer injury when “the passenger car has a frontal impact with a heavier passenger car,” “the passenger car has a frontal impact with an LTV/SUV, truck,” and “the passenger car is side impacted by an LTV/SUV,” or the like. These examples should be recognized as clear cases of incompatibility. This paper will describe an approach which aim at improving compatibility. However, around 60% of occupants who suffer fatal injuries are not wearing a seat belt.

Tire-pavement interaction noise (TPIN) is a dominant source for passenger cars and trucks above 40 km/h and 70 km/h, respectively. TPIN is mainly generated from the interaction between the tire and the pavement. In this paper, twenty-two passenger car radial (PCR) tires of the same size (16 in. radius) but with different tread patterns were tested on a non-porous asphalt pavement. For each tire, the noise data were collected using an on-board sound intensity (OBSI) system at five speeds in the range from 45 to 65 mph (from 72 to 105 km/h). The OBSI system used an optical sensor to record a once-per-revolution signal to monitor the vehicle speed. This signal was also used to perform order tracking analysis to break down the total tire noise into two components: tread pattern-related noise and non-tread pattern-related noise.

The Hybrid Electric Vehicle Team of Virginia Tech (HEVT) is participating in the 2008 - 2011 EcoCAR: The NeXt Challenge Advanced Vehicle Technology Competition series organized by Argonne National Laboratory (ANL) and sponsored by General Motors (GM) and the U.S. Department of Energy (DoE). Following GM's vehicle development process, HEVT established goals that meet or exceed the competition requirements for EcoCAR in the design of a plug-in, range-extended hybrid electric vehicle. The challenge involves designing a crossover SUV powertrain to reduce fuel consumption, petroleum energy use and well-to-wheels (WTW) greenhouse gas (GHG) emissions. In order to interface with and control the vehicle, the team added a National Instruments (NI) CompactRIO (cRIO) to act as a hybrid vehicle supervisory controller (HVSC).

Improving fuel economy and overall vehicle emissions are very important in today's society with strict new regulations throughout the world. To help in the education process for the next generation of design engineers, this paper seeks to define a powertrain model created and developed to help users understand the basics behind hybrid vehicles and the effects of these advanced technologies. One of the main goals of this research is to maintain a simplified approach to model development. The 1 Hz model described within this work aims to allow energy to be simply and understandably traced through a hybrid powertrain. Through the use of a “backwards” energy tracking method, demand for a drive cycle is found, and, after tracing the energy demand through each powertrain component, the resulting fuel to meet vehicle demand and associated powertrain losses is found.

Event data recorders (EDRs) must survive regulatory frontal and side compliance crash tests if installed within a car or light truck built on or after September 1, 2012. Although previous research has shown that EDR data are surviving these tests, little is known about whether EDRs are capable of surviving collisions of higher delta-v, or crashes involving vehicle fire or immersion. The goal of this study was to determine the survivability of light vehicle EDRs in real world fire, immersion, and high change in velocity (delta-v) cases. The specific objective was to identify the frequency of these extreme events and to determine the EDR data download outcome when subject to damage caused by these events. This study was performed using three crash databases: the Fatality Analysis Reporting System (FARS), the National Automotive Sampling System / Crashworthiness Data System (NASS/CDS), and the National Motor Vehicle Crash Causation Survey (NMVCCS).

Routing quality always dominates the top 20% of in vehicle- navigation customer complaints. In vehicle navigation routing engines do not customize results based on customer behavior. For example, some users prefer the quickest route while some prefer direct routes. This is because in vehicle navigation systems are traditionally embedded systems. Toyota announced that new model vehicles in JP, CN, US will be connected with routing function switching from the embedded device to the cloud in which there are plenty of probe data uploaded from the vehicles. Probe data makes it possible to analyze user preferences and customize routing profile for users. This paper describes a method to analyze the user preferences from the probe data uploaded to the cloud. The method includes data collection, the analysis model of route scoring and user profiling. Furthermore, the evaluation of the model will be introduced at the end of the paper.

The use of hydrogen produced from renewable energy sources is expected to be one of the most promising options for achieving carbon neutrality in automobiles, in addition to electrification and the use of biofuels and synthetic fuels. In recent years, along with fuel cell electric vehicles (FCEVs), there has been renewed interest in hydrogen engines that can utilize internal combustion engine technology. Although hydrogen has the property of a high laminar burning velocity and a wide flammable range compared to other fuels, the actual combustion phenomenon in a real engine is strongly influenced by the turbulence created by the in- cylinder flow and the distribution of fuel and air in the cylinder due to the formation of the mixture. Therefore, to fully utilize hydrogen as a fuel in actual engines and bring out its performance, it is important to understand the basic combustion characteristics of hydrogen in the cylinder and the effects of these factors on hydrogen combustion.

Vehicle analytical models are often favorable due to describing the physical phenomena associated with vehicle operation following from the principles of physics, with explainable mathematical trends and with extendable modeling to other types of vehicle. However, no experimentally validated analytical model has been developed as yet of diesel engine fuel consumption rate. The present paper demonstrates and validates for trucks and light commercial vehicles an analytical model of supercharged diesel engine fuel consumption rate. The study points out with 99.6% coefficient of determination that the average percentage of deviation of the steady speed-based simulated results from the corresponding field data is 3.7% for all Freeway cycles. The paper also shows with 98% coefficient of determination that the average percentage of deviation of the acceleration-based simulated results from the corresponding field data under negative acceleration is 0.12 %.