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This paper focuses on an inherent problems of active damping control prevalent in contemporary hybrid torque controls. Oftentimes, a supervisory torque controller utilizes simplified system models with minimal system states representation within the optimization problem, often not accounting for nonlinearities and stiffness. This is motivated by enabling the generation of the optimum torque commands with minimum computational burden. When inherent lash and stiffness of the driveline are not considered, the resulting command can lead to vibrations and oscillations in the powertrain, reducing performance and comfort. The paper proposes a Linear Quadratic Integral (LQI)-based compensator to be integrated downstream the torque supervisory algorithm, which role is to shape transient electric machine torques, compensating for the stiffness and backlash present in the vehicle while delivering the driver-requested wheel torque.

This paper is the fourth printed listing of the National Highway Traffic Safety Administration’s (NHTSA) center-of-gravity (CG) location measurements. The previous papers contained data for 1024 vehicles. This paper includes data for 448 additional vehicles tested as part of NHTSA’s New Car Assessment Program (NCAP) for the years 2009 through year 2020. The NCAP involves only the CG location measurement; so the vehicles listed in this paper do not have inertial data.

Electric vehicles (EVs) and the development around them has been rapid in recent years. As the battery is the most essential component of an electric vehicle, a lot of research and analysis has been focused on ensuring safe and reliable performance of batteries. Considering the location, size, and operating conditions for EV batteries, they must be designed with an in-built safety infrastructure keeping in mind certain realistic scenarios such as fire exposure, mechanical vibration, collisions, over-charging, single cell failures, and others. In this paper, we discuss an overview of various EV battery failure mechanisms, present current safety and abuse testing methods and standards associated with such mechanisms and discuss the need for the development and implementation of additional testing standards to better characterize the safety performance of EV battery packs.

Battery electric transit buses sold in Canada generally include a fuel-fired diesel auxiliary heater for cabin heating in cold weather. This report details a test project, performed in collaboration with OC Transpo, to capture and quantify the emissions from such a fuel-fired heater (FFH) installed on a New Flyer XE40 battery electric transit bus from OC Transpo’s fleet in Ottawa, Canada. The FFH was tested while the bus was both stationary and being driven on-road in cold conditions. The results include the emissions rates of carbon dioxide, carbon monoxide, nitrogen oxides, hydrocarbons and methane, and soot. Additionally, total particulate matter results were obtained during stationary testing. The results of stationary testing were compared to the California Air Resources Board and European Union standards for FFH emissions, even though these standards do not apply directly to buses operated outside of these jurisdictions.

Scientific methodology and engineering techniques were applied to a series of three automobile rear-end collision experiments to provide data relating to seat, seat backrest, and head-restraint design. Five seat back heights and four seat back strength values were studied in connection with their practicality and relative protective features, when subjected to a 55 mph rear-end collision exposure. These research data provide a basic reference system of high-speed collision performance for seat designs with respect to occupant size and proximity to injury producing structures. Additionally, methodology, instrumentation, and related equipment required for post-crash fire studies were included in experiment 106, providing what is believed to be the first published data on the precise time-related events associated with collision-induced passenger car fires. Design revisions suggested by these findings are discussed.

The recent demand for power generation capability has raised the operating temperature of the power plants in the range of 600°C. High operating temperature leads to material degradation or reduced lifespan of boilers, which necessitates the analysis of the high-temperature behavior of welded joints of power plant boilers for a long lifespan and improved efficiency. Gr91 martensitic and SS304 austenitic stainless steel are identified as the primary piping material for these boilers. The boiler piping involves similar weld joints (Gr91/Gr91 and SS304/SS304) and dissimilar weld joints (SS304/Gr91) known as transition joints. These joints are exposed to high temperatures for a long duration during their service and it is therefore necessary to evaluate the high-temperature behavior of these weld joints. The hot tensile test is a short-term high-temperature test that serves as a valuable tool for analyzing the high-temperature behavior of the welds.

Engine operation produces particles that contaminate the lubricating oil and can damage the engine's internal components. This paper presents a model for a three-coil inductive metal particle sensor and verifies the rationality and accuracy of the model by simulating the motion of a single spherical iron particle passing through the sensor. On this basis, the simulation of coupling double particles with different sizes, distances, and shapes is carried out. The study explores the influence of particle motion on the sensor-induced signal under various conditions. The research shows that when two particles pass through the sensor, the induced voltage signal will produce superposition when the distance between the two particles is small. The peak value of the induced voltage is 1-2 times the peak value of the induced voltage of a single particle. As the distance increases, the peak value of the induced voltage initially decreases, then slowly increases, and finally stabilizes.

This research aims to develop an inverse control method capable of adaptively simulating dynamic models of car subsystems in the rig-test condition. Accurate simulation of the actual vibration conditions is one of the most crucial factors in realizing reliable rig-test platforms. However, most typical rig tests are conducted under simple random or harmonic sweep conditions. Moreover, the conventional test methods are hard to directly adapt to the actual vibration conditions when switching the dynamic characteristics of the subsystem in the rig test. In the present work, we developed an inverse controller to adaptively control the vibration exciter referring to the target vibration signal. An adaptive LMS filter, employed for the control algorithm, updated the filter weights in real time by referring to the target and the measured acceleration signals.

Broadband active noise control algorithms require high-performance so multi-channel control to ensure high performance, which results in very high computational power and expensive DSP. When the control filter update part need a huge computational power of the algorithm is separated and calculated by the server, it is possible to reduce cost by using a low-cost DSP in a local vehicle, and a performance improvement algorithm requiring a high computational power can be applied to the server. In order to achieve the above goal, this study analyzed the maximum delay time when communication speed is low and studied response measures to ensure data integrity at the receiving location considering situations where communication speed delay and data errors occur.

Autonomous driving is a hot topic in the automotive domain, and there is an increasing need to prove its reliability. They use machine learning techniques, which are themselves stochastic techniques based on some kind of statistical inference. The occurrence of incorrect decisions is part of this approach and often not directly related to correctable errors. The quality of the systems is indicated by statistical key figures such as accuracy and precision. Numerous driving tests and simulations in simulators are extensively used to provide evidence. However, the basis of all descriptive statistics is a random selection from a probability space. The difficulty in testing or constructing the training and test data set is that this probability space is usually not well defined. To systematically address this shortcoming, ontologies have been and are being developed to capture the various concepts and properties of the operational design domain.

Range anxiety in current battery electric vehicles is a challenging problem, especially for commercial vehicles with heavy payloads. Therefore, the development of electrified propulsion systems with multiple power sources, such as fuel cells, is an active area of research. Optimal speed planning and energy management, referred to as eco-driving, can substantially reduce the energy consumption of commercial vehicles, regardless of the powertrain architecture. Eco-driving controllers can leverage look-ahead route information such as road grade, speed limits, and signalized intersections to perform velocity profile smoothing, resulting in reduced energy consumption. This study presents a comprehensive analysis of the performance of an eco-driving controller for fuel cell electric trucks in a real-world scenario, considering a route from a distribution center to the associated supermarket.

In the diagnosis of membrane flooding and drying faults in a Proton Exchange Membrane Fuel Cell (PEMFC) through Electrochemical Impedance Spectroscopy (EIS), this paper proposes a Genetic Algorithm (GA)-based feature selection method for selecting the required frequency points of failure, to reduce the measurement time taken by EIS while ensuring high diagnostic accuracy. This feature selection method searches the feature space through GA and proposes an encoding method tailored to this problem. During the searching process, three algorithms, i.e., Backpropagation Neural Network (BPNN), K-Nearest Neighbor (KNN), and eXtreme Gradient Boosting (XGBoost), are used to extract various features and select higher diagnostic rates of feature frequencies.

Optimizing fuel injection spray is essential to comply with stringent future emission regulations for hybrid vehicles and internal combustion engine vehicles, and the spray characteristics and geometry must be robust for various engine operating conditions. This study presents experimental and numerical assessments of spray for lateral-mounted gasoline direct injection (GDI) sprays with different plume arrangements to analyze collapse characteristics, which can significantly deteriorate the geometry and characteristics of fuel sprays. Novel spray characterization methods are applied to analyze complex spray collapse behaviors using LED-based diffusive back-illuminated extinction imaging (DBIEI) and 3D computed tomographic (CT) image reconstruction. High-fidelity computational fluid dynamics (CFD) simulations are performed to analyze the detailed spray characteristics besides experimental characterization.

The goal of this study was to use naturalistic driving data to characterize the motion of vehicles making right turns at signalized intersections. Right-turn maneuvers from 13 intersections were extracted from the Second Strategic Highway Research Program (SHRP2) database and categorized based on whether or not the vehicle came to a stop prior to making its turn. Out of the vehicles that did stop, those that were the first and second in line at the intersection were isolated. This resulted in 186 stopped first-in-line turns, 91 stopped second-in-line turns, and 353 no stop turns. Independent variables regarding the maneuver, including driver’s sex and age, vehicle type, speed, and longitudinal and lateral acceleration were extracted. The on-board video was reviewed to categorize the road as dry/wet and if it was day/night. Aerial photographs of the intersections were obtained, and the inner radius of the curve was measured using the curb as a reference.

A considerable amount of research has been conducted to evaluate the effects of road surface discontinuities and disturbances on vehicle dynamics and accident causation. This paper addresses the real world effects of these conditions by reviewing the analyses of actual physical evidence of accidents involving alleged road defects. Analysis and testing techniques are described and alternative causative elements are presented.

When developing an airbag system with mechanical sensors, one of the important stages is to get satisfactory correlation between the sensor characteristics and the specific vehicle. This development stage requires control of both vehicle crashworthiness (including selection of sensor mount location) and airbag sensor characteristics. This stage is ordinarily performed through many iterations of a computer simulation which involves the dynamic structure of the sensor mechanism. A new graphic method is proposed in this paper to help in this simulation stage. This method can estimate the proper threshold level of the crash sensor. The airbag sensor mount location in the vehicle can be selected and the airbag sensor can be developed. The validity of the method has been verified by computer simulation as well as actual test results.

An indoor road-wheel facility at the Technical University of Gdańsk was used to study the noise emission from a variety of tires with different tread patterns. The tires were run both on a smooth steel drum and a drum covered by a replica road surface. All tread patterns were hand-cut to generate several families of simple treads with regular pitch for a systematic study of how groove design influences noise. Most of the observed, tread influenced phenomena could be explained by generation mechanisms such as radial vibrations induced by tread block impact, pocket air pumping and pipe resonances in the grooves. For instance, it was observed that, when speed increases, sooner or later the tread block impact frequency will coincide with the pipe resonance frequency and then generate excessive noise at that speed.

This paper outlines the characteristics of rollover accidents based on a representative sample of British cars and light vans. The data come from on-the-spot and follow up investigations of accidents conducted by Birmingham University and the Ford Motor Company in which damaged vehicles were examined and information from them correlated with injury data obtained from hospitals. Rollovers are either initiated by impact with another vehicle or are simple rolls, the incidence of other types of roll being low. Door opening rates are shown to be high, and the character of roof collapse, in terms of position and amount, is described. The sources of injury to occupants is discussed. Injury to the head or face occurred in 96% of injured occupants. Seat belts, when worn, prevent ejection but cannot offer complete immunity from injury in this type of accident. Some improvements in crash performance are outlined and a tentative testing procedure is mentioned.