Search Results

The Chevy Bolt’s One Pedal Driving feature is a new electrification propulsion enhancement that allows the driver to accelerate, decelerate and hold their vehicle stationary by just using the accelerator pedal. With this new feature, the driver is relieved of having to switch between pressing the accelerator pedal and brake pedal to slow, stop and hold the vehicle stationary. While this feature provides a convenience to the driver, it also presents a paradigm shift in driver engagement and control system responsibility for executing certain functions that the driver was traditionally responsible to perform. Various system safety techniques were involved in the development of such a feature both from a traditional functional safety perspective as well as a Safety of the Intended Functionality (SOTIF) perspective.

The overall technology trend of Active Safety and Driver Assistance systems is relatively clear: increasing capability to avoid crashes as well as convenience on a path toward autonomous driving. What's less obvious, though, is the selection of features/technologies will make sense at each step along the path. Specific vehicle contenting decisions get made early in the vehicle planning process and rely on forecasting factors such as technology readiness, consumer interest, the economics in the supply base, and projected government regulations and consumer metrics. Additionally, for these technologies to be effective, often they need to be introduced in conjunction with other features and grouped in ways that are intuitive and relevant to current consumer needs.

Automotive technology is rapidly changing with electrification of vehicles, driver assistance systems, advanced safety systems etc. This advancement in technology is making the task of validation and verification of embedded software complex and challenging. In addition to the component testing, integration testing imposes even tougher requirements for software testing. To meet these challenges dSPACE is continuously evolving the Hardware-In-the-Loop (HIL) technology to provide a systematic way to manage this task. The paper presents developments in the HIL hardware technology with latest quad-core processors, FPGA based I/O technology and communication bus systems such as Flexray. Also presented are developments of the software components such as advanced user interfaces, GPS information integration, real-time testing and simulation models. This paper provides a real-world example of implication of integration testing on HIL environment for Chassis Controls.

Injury Risk Curves are developed from cadaver data for sternal deflections produced by anterior, distributed chest loads for a 25, 45, 55, 65 and 75 year-old Small Female, Mid-Size Male and Large Male based on the variations of bone strengths with age. These curves show that the risk of AIS ≥ 3 thoracic injury increases with the age of the person. This observation is consistent with NASS data of frontal accidents which shows that older unbelted drivers have a higher risk of AIS ≥ 3 chest injury than younger drivers.

Level 2 (L2) partial driving automation systems are rapidly emerging in the marketplace. L2 systems provide sustained automatic longitudinal and lateral vehicle motion control, reducing the need for drivers to continuously brake, accelerate and steer. Drivers, however, remain critically responsible for safely detecting and responding to objects and events. This paper summarizes variations of L2 systems (hands-on and/or hands-free) and considers human drivers’ roles when using L2 systems and for designing Human-Machine Interfaces (HMIs), including Driver Monitoring Systems (DMSs). In addition, approaches for examining potential unintended consequences of L2 usage and evaluating L2 HMIs, including field safety effect examination, are reviewed. The aim of this paper is to guide L2 system HMI development and L2 system evaluations, especially in the field, to support safe L2 deployment, promote L2 system improvements, and ensure well-informed L2 policy decision-making.

The purchase of a new automobile is unquestionably a significant investment for most customers, and with this recognition, comes a correspondingly significant expectation for quality and reliability. Amongst automotive systems -when it comes to considerations of reliability - the brakes (perhaps along with the tires) occupy a rarified position of being located in a harsh environment, subjected to continuous wear throughout their use, and are critical to the safe performance of the vehicle. Maintenance of the brake system is therefore a fact of life for most drivers - something that almost everyone must do, yet given the potentially considerable expense, it is something that of great benefit to minimize.

Seat lateral support is often talked about as a design parameter, but usually in terms of psychological perception. There are many difficulties in quantifying lateral support mechanically to the engineering teams: Anthropometric variation causes different people to interact with the seat in different places and at different angles, BPD studies are usually planar and don’t distinguish between horizontal support and vertical resistance to sinking in, most mechanical test systems are typically single-DOF and can’t apply vertical and horizontal loads concurrently, and there is scant literature describing the actual lateral loads of occupants. In this study, we characterize the actual lateral loading on example seating from various sized/shaped occupants according to dynamic pressure distribution. From this information, a six-DOF load and position control test robot (KUKA OccuBot) is used to replicate that pressure distribution.

Low-temperature gasoline combustion (LTGC) engines can provide high efficiencies and extremely low NOx and particulate emissions, but controlling the combustion timing remains a challenge. This paper explores the potential of Partial Fuel Stratification (PFS) to provide fast control of CA50 in an LTGC engine. Two different compression ratios are used (CR=16:1 and 14:1) that provide high efficiencies and are compatible with mixed-mode SI-LTGC engines. The fuel used is a research grade E10 gasoline (RON 92, MON 85) representative of a regular-grade market gasoline found in the United States. The fuel was supplied with a gasoline-type direct injector (GDI) mounted centrally in the cylinder. To create the PFS, the GDI injector was pulsed twice each engine cycle. First, an injection early in the intake stroke delivered the majority of the fuel (70 - 80%), establishing the minimum equivalence ratio in the charge.

Hybrid and electric vehicles utilize high power electric motors to propel the vehicle requiring a significant level of electric current to travel between various modules such as energy storage devices, power inverter modules, energy charging modules, and the motors themselves. This electric current creates magnetic fields around the devices themselves and wiring that delivers this current between devices within the vehicle. These devices and wiring exist throughout the vehicle and can even exist near vehicle occupants, which has prompted investigations looking into the short term biological effect these non-ionizing fields can have on the human body. The findings from these investigations have been published by organizations such as the International Commission on Non-Ionizing Radiation Protection (ICNIRP), and some nations have passed laws regulating the magnetic and electric field exposure to vehicle occupants.

There has been an increasing interest in exploring the potential to reduce energy consumption of future connected and automated vehicles. People have extensively studied various eco-driving implementations that leverage preview information provided by on-board sensors and connectivity, as well as the control authority enabled by automation. Quantitative real-world evaluation of eco-driving benefits is a challenging task. The standard regulatory driving cycles used for measuring exhaust emissions and fuel economy are not truly representative of real-world driving, nor for capturing how connectivity and automation might influence driving trajectories. To adequately consider real-world driving behavior and potential “off-cycle” impacts, this paper presents four collaborative evaluation methods: large-scale simulation, in-depth simulation, vehicle-in-the-loop testing, and vehicle road testing.

The implementation of electronic shifters (e-shifter) for automatic transmissions in vehicles has created many new opportunities for the customer facing transmission interface and in-vehicle packaging. E-shifters have become popular in recent years as their smaller physical size leads to packaging advantages, they reduce the mass of the automatic transmission shift system, they are easier to install during vehicle assembly, and act as an enabler for autonomous driving. A button-style e-shifter has the ability to create a unique customer interface to the automatic transmission, as it is very different from the conventional column lever or linear console shifter. In addition to this, a button-style e-shifter can free the center console of valuable package space for other customer-facing functions, such as storage bins and Human-Machine Interface controllers.

Since steering wheel torque feedback is one of the crucial factors for drivers to gain road feel and ensure driving safety, it is especially important to simulate the steering torque feedback for a driving simulator. At present, steering wheel feedback torque is mainly simulated by an electric motor with gear transmission. The torque response is typically slow, which can result in drivers’ discomfort and poor driving maneuverability. This paper presents a novel torque feedback device with magnetorheological (MR) fluid and coil spring. A phase separation control method is also proposed to control its feedback torque, including spring and damping torques respectively. The spring torque is generated by coil spring, the angle of coil spring can be adjusted by controlling a brushless DC motor. The damping torque is generated by MR fluid, the damping coefficient of MR fluid can be adjusted by controlling the current of excitation coil.

This article presents experimental results obtained with a disruptive engine platform, designed to maximize the engine efficiency through a synergetic implementation of downsizing, high compression-ratio, and importantly exhaust-heat energy recovery in conjunction with advanced lean/dilute low-temperature type combustion. The engine architecture is a supercharged high-power output, 1.1-liter engine with two-firing cylinders and a high compression ratio of 13.5: 1. The integrated exhaust heat recovery system is an additional, larger displacement, non-fueled cylinder into which the exhaust gas from the two firing cylinders is alternately transferred to be further expanded. The main goal of this work is to implement in this engine, advanced lean/dilute low-temperature combustion for low-NOx and high efficiency operation, and to address the transition between the different operating modes.

In this paper, a driver identification scheme is studied using general driver inputs such as accelerating, braking and steering behavior, in addition to the settings related to driver’s physical characteristics, such as driver’s seat position. Several drivers are selected with various ages, genders and driving skills to participate in the study. Their driving data is collected using the same test vehicle, and while driving on the same routes. This helps eliminate the inherent vehicle to vehicle variations and the impact of the route differences and enables the identification algorithm to focus on the driving behavior. The driving routes are broken down into shorter segments where the driving features are calculated and populated in these segments. To reduce the identification bias towards certain rare events in the ride, the features are reset at the beginning of each trip segment. This additionally helps to ensure that there is no spill of feature values across the segments.

Due to growing interest in automated driving, the need for better understanding of human driving behavior in uncertain environment, such as driving behavior at un-signalized crossroad and roundabout, has further increased. Driving behavior at roundabout is greatly influenced by different dynamic factors such as speed, distance and circulating flow of the potentially conflicting vehicles, and drivers should choose whether to leave or wait at the upcoming exit according to these factors. In this paper, the influential dynamic factors and driving behavior characteristics at the roundabout is analyzed in detail, random forest method is then deployed to predict the driving behavior. For training the driving behavior model, four typical roundabout layouts were created under a real-time driving simulator with PanoSim-RT and dSPACE. Traffic participants with different motion style were also set in the simulation platform to mimic real driving conditions.

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.

Methanol is currently being evaluated as a promising alternative fuel for internal combustion engines, due to being attainable by carbon neutral or negative pathways (renewable energy and carbon capture technology). The low ignitability of methanol has made it attractive mostly as a fuel for spark ignition engines, however the low sooting properties of the fuel could potentially reduce the NOx-soot tradeoff present in compression ignition engines. In this work, using a 4-cylinder engine with compression ratio modified from 16:1 to 19:1, methanol combustion is evaluated under five operating conditions in terms of fuel consumption, criteria pollutants, CO2 emissions and engine efficiency in addition to the qualitative assessment of the combustion stability. It was found that combustion is stable at medium to high loads, with medium load NOx emissions levels at least 30% lower than the original diesel engine and comparable emissions at maximum load conditions.

De-fossilization is an increasingly important trend in the energy sector. In the transport sector the de-fossilization efforts have been centered in promoting the electrification of vehicles, nonetheless other pathways, like the use of carbon neutral or carbon-offsetting fuels under current vehicle fleets, are also worth considering. Low-carbon fuels (LCF) can be synthetized from sources that can take advantage of the carbon already present in the atmosphere (either by technologies like direct carbon capture or biological processes like photosynthesis in biofuels) and use energy from renewable sources for the necessary industrial processes. Although, LCFs can be compared to fossil fuels as energy sources for internal combustion engines, their composition is not the same and their properties can modify the engine combustion and emissions.

Fuel lean combustion and exhaust gas dilution are known to increase the thermal efficiency and reduce NOx emissions. In this study, experiments are performed to understand the effect of equivalence ratio on flame kernel formation and flame propagation around the spark plug for different low turbulent velocities. A series of experiments are carried out for propane-air mixtures to simulate engine-like conditions. For these experiments, equivalence ratios of 0.7 and 0.9 are tested with 20 percent mass-based exhaust gas recirculation (EGR). Turbulence is generated by a shrouded fan design in the vicinity of J-spark plug. A closed loop feedback control system is used for the fan to generate a consistent flow field. The flow profile is characterized by using Particle Image Velocimetry (PIV) technique. High-speed Schlieren visualization is used for the spark formation and flame propagation.

Knee airbags (KABs) are one countermeasure in newer vehicles that could influence lower extremity (LEX) injury, the most frequently injured body region in frontal crashes. To determine the effect of KABs on LEX injury for drivers in frontal crashes, the analysis examined moderate or greater LEX injury (AIS 2+) in two datasets. Logistic regression considered six main effect factors (KAB deployment, BMI, age, sex, belt status, driver compartment intrusion). Eighty-five cases with KAB deployment from the Crash Injury Research and Engineering Network (CIREN) database were supplemented with 8 cases from the International Center for Automotive Medicine (ICAM) database and compared to 289 CIREN non-KAB cases. All cases evaluated drivers in frontal impacts (11 to 1 o’clock Principal Direction of Force) with known belt use in 2004 and newer model year vehicles. Results of the CIREN/ICAM dataset were compared to analysis of a similar dataset from NASS-CDS (5441 total cases, 418 KAB-deployed).