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Abstract This study aims to take the first step in bridging the gap between vehicle dynamics systems and autonomous control strategies research. More specifically, a nested method is employed to evaluate the collision avoidance ability of autonomous vehicles in the primary design stage theoretically based on both dynamics and control parameters. An integrated model is derived from a half car mathematical model in the lateral direction, consisting of two degrees of freedom, lateral deviation and yaw angle, with a traction mathematical model in the longitudinal direction, consisting of two degrees of freedom, the longitudinal velocity and rolling velocity of the wheel. The integrated model uses a mathematical power train model to generate the torque on the wheel and connects the two systems via the magic formula tyre model to represent the tyre non-linearity during augmented longitudinal and lateral dynamic attitudes.

Abstract Gasoline particulate filters (GPFs) are important aftertreatment components that enable gasoline direct injection (GDI) engines to meet European Union (EU) 6 and China 6 particulate number emissions regulations for nonvolatile particles greater than 23 nm in diameter. GPFs are rapidly becoming an integral part of the modern GDI aftertreatment system. The Active Exhaust Tuning (EXTUN) Valve is a butterfly valve placed in the tailpipe of an exhaust system that can be electronically positioned to control exhaust noise levels (decibels) under various vehicle operating conditions. This device is positioned downstream of the GPF, and variations in the tuning valve position can impact exhaust backpressures, making it difficult to monitor soot/ash accumulation or detect damage/removal of the GPF substrate. The purpose of this work is to present a unique example of subsystem control and diagnostic architecture for an exhaust system combining GPF and EXTUN.

Abstract This article presents a fault diagnosis approach for roller bearing by applying the autocorrelation approach to filtered vibration measured signal. An optimal Morlet wavelet filter is applied to eliminate the frequency associated with interferential vibrations; the raw measured signal is filtered with a band-pass filter based on a Morlet wavelet function whose parameters are optimized based on maximum Kurtosis. Autocorrelation enhancement is applied to the filtered signal to further reduce the residual in-band noise and highlight the periodic impulsive feature. The proposed technique is used to analyze the experimental measured signal of investigated vehicle gearbox. An artificial fault is introduced in vehicle gearbox bearing an orthogonal placed groove on the inner race with the initial width of 0.6 mm approximately. The faulted bearing is a roller bearing located on the gearbox input shaft - on the clutch side.

Abstract This article applies a new method for the evaluation and estimation of real-life energy consumption of two different thermal management systems based on driving behavior in the course of the day. Recent attempts to find energy-efficient thermal management systems for electric and plug-in hybrid electric vehicles have led to using secondary loop systems as an alternative approach for meeting dynamic heating and cooling demands and reducing refrigerant charge. However, the additional layer of thermal resistance, which influences the system’s transient behavior as well as passenger compartment comfort during cool-down or heat-up, makes it difficult to estimate the annual energy consumption. In this article, the overall energy consumption of a conventional and a secondary loop system is compared using a new method for describing actual customers’ driving behavior in the course of the day.

Abstract Making use of a specifically designed dynamical vehicle model, the authors here presented the results of an activity for the evaluation of energy consumption and CO2 emissions of buses for urban applications. Both conventional and innovative (series hybrid, and fully electric) vehicles were considered to obtain interesting comparative conclusions. The derived tool was used to simulate the dynamical behaviour of these vehicles on a number of kinematic profiles measured during real buses operation in different contexts, varying from really congested city centre routes to fast-lane operated services. It was so possible to evaluate the energetic performances of those buses on a Tank-to-Wheel (TTW) basis.

Abstract The development, analysis, and optimization of battery electric class-7 heavy-duty trucks equipped with multi-speed transmissions are discussed in this paper. The designs of five new traction motors-fractional-slot, concentrated winding machines-are proposed for use in heavy-duty electric trucks. The procedure for gear-ratio range selection is outlined and ranges of gear ratios for three-to six-speed transmission powertrains are calculated for each of the proposed electric traction motors. The simulation and gear-ratio optimization tasks for class-7 battery electric trucks are formulated. The energy consumption of the e-truck with the twenty possible powertrain combinations is minimized over the four driving cycles and the most efficient powertrain layouts that meet the performance criteria are recommended.

Abstract This article presents a comprehensive investigation for the interaction between vehicle ride vibration control and braking control using two degrees of freedom (2DOF) quarter vehicle model. A typical limited bandwidth active suspension system with nonlinear spring and damping characteristics of practical hydraulic and pneumatic components is controlled to regulate both suspension and tire forces and therefore provide the optimum ride comfort and braking performance of an anti-lock brake system (ABS). In order to design a suitable controller for this nonlinear integrated system, various control techniques are followed including state feedback tuned using Linear Quadratic Regulator (LQR), state feedback tuned using Genetic Algorithm (GA), Proportional Integrated (PI) tuned genetically, and Fuzzy Logic Control (FLC). The ABS control system is designed to limit skid ratio below threshold of 15%.

Abstract Tire-pavement interaction noise (TPIN) dominates for passenger cars above 40 km/h and trucks above 70 km/h. Numerous studies have attempted to uncover and distinguish the basic mechanisms of TPIN. However, intense debate is still ongoing about the validity of these mechanisms. In this work, the physical mechanisms proposed in the literature were reviewed and divided into three categories: generation mechanisms, amplification mechanisms, and attenuation mechanisms. The purpose of this article is to gather the published general opinions for further open discussions.

Abstract The high-frequency noise issue is one of the most significant noise, vibration, and harshness problems, particularly in battery electric vehicles (BEVs). The sound package treatment is one of the most important approaches toward solving this problem. Owing to the limitations imposed by manufacturing error, assembly error, and the operating conditions, there is often a big difference between the actual values and the design values of the sound package components. Therefore, the sound package parameters include greater uncertainties. In this article, an uncertainty analysis method for BEV interior noise was developed based on an interval model to investigate the effect of sound package uncertainty on the interior noise of a BEV. An interval perturbation method was formulated to compute the uncertainty of the BEV’s interior noise.

Abstract The dynamic characteristics of tires are critical in the overall vibrations of vehicles because the tire-road interface is the only medium of energy transfer between the vehicle and the road surface. Obtaining the natural frequencies and mode shapes of the tire helps in improving the comfort of the passengers. The vibrational characteristics of structures are usually obtained by performing conventional impact hammer modal testing, in which the structure is excited with an impact hammer and the response of the structure under excitation is captured using accelerometers. However, this approach only provides the response of the structure at a few discrete locations, and it is challenging to use this procedure for rotating structures. Digital Image Correlation (DIC) helps in overcoming these challenges by providing the full-field response of the structure.

Abstract Correlation analysis of subjective and objective evaluation for automobile sound quality is an important topic in automobile technology fields. In view of the deficiency of multi-dimensional linear regression analysis and the theoretical merits of grey system method, grey comprehensive relational degree was calculated to analyze the contribution of objective evaluation data to subjective evaluation. The main objective variables affecting the subjective feeling were determined. The variables include loudness, sharpness and shaking degrees. Grey GM(0,4) model was established as a quantitative expression for describing the subjective and objective evaluation correlation. The results of residual test and posterior-variance-test show that the established model was accurate and the model can be used to analyze and predict subjective and objective evaluation data of automobile sound quality.

Abstract Dynamic stresses exist in parts of a catalyst muffler caused by the vibration of a moving vehicle, and it is important to clarify and predict the vibration response properties for preventing fatigue failures. Assuming a vibration isolating installation in the vehicle frame, the vibration transmissibility and local dynamic stress of the catalyst muffler were examined through a vibration machine. Based on the measured data and by systematically taking vibration theories into consideration, a new prediction method of the vibration modes and parameters was proposed that takes account of vibration isolating and damping. A lumped vibration model with the six-element and one mass point was set up, and the vibration response parameters were analyzed accurately from equations of motion. In the vibration test, resonance peaks from the hanging bracket, rubber bush, and muffler parts were confirmed in three excitation drives, and local stress peaks were coordinate with them as well.

Abstract Recently, electric heavy-duty tractor-trailers (EHDTTs) have assumed significance as they present an immediate solution to decarbonize the transportation sector. Hence, to illustrate the economic viability of electrifying the freight industry, a detailed numerical model to estimate the battery capacity for an EHDTT is proposed for a route between Washington, DC, to Knoxville, TN. This model incorporates the effects of the terrain, climate, vehicular forces, auxiliary loads, and payload in order to select the appropriate motor and optimize the battery capacity. Additionally, current and near-future battery chemistries are simulated in the model. Along with equations describing vehicular forces based on Newton’s second law of motion, the model utilizes the Hausmann and Depcik correlation to estimate the losses caused by the capacity offset of the batteries. Here, a Newton-Raphson iterative scheme determines the minimum battery capacity for the required state of charge.

Abstract Electric heavy-duty tractor-trailers (EHDTT) offer an important option to reduce greenhouse gases (GHG) for the transportation sector. However, to increase the range of the EHDTT, this effort investigates critical vehicle design features that demonstrate a gain in overall freight efficiency of the vehicle. Specifically, factors affecting aerodynamics, rolling resistance, and gross vehicle weight are essential to arrive at practical input parameters for a comprehensive numerical model of the EHDTT, developed by the authors in a subsequent paper. For example, drag reduction devices like skirts, deturbulators, vortex generators, covers, and other commercially available apparatuses result in an aggregated coefficient of drag of 0.367. Furthermore, a mixed utilization of single-wide tires and dual tires allows for an optimized trade-off between low rolling resistance tires, traction, and durability.

Abstract The following article illustrates the detailed study of the development of a unique flywheel-based regenerative braking system (f-RBS) for achieving regenerative braking in a commercial electric bus. The f-RBS is designed for installation in the front wheels of the bus. The particular data values for modeling the bus are taken from multiple legitimate sources to illustrate the development strategy of the regenerative braking system. Mechanical components used in this system have either been carefully designed and analyzed for avoiding fatigue failure or their market selection strategies explained. The positioning of the entire system is decided using MSC Adams View®, hence determining a suitable component placement strategy such that the f-RBS components do not interfere with the bus components. The entire system is modeled on MATLAB Simulink® with sufficient accuracy to get various results that would infer the performance of the system as a whole.

Abstract This article presents the application of the Life Cycle Sustainability Assessment (LCSA) methodology for integrating environmental, economic, and social assessment results by the direct application of Fuzzy-Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). The aim of this work is to test the applicability of LCSA methodology as a potential tool to support the design phase, providing solutions tailored to its application in the automotive sector. To validate the proposed procedure, two alternative design solutions for a car dashboard are used as case study. In response to the need of methods and tools for evaluating and comparing sustainability of alternative design solutions, LCSA is seen as one of the most promising method, but which needs further testing with real cases to solve some methodological challenges.

Abstract In the selection of automobile noise reduction schemes, the lack of comprehensive quantitative index system and objective evaluation method is a serious problem. In this article, the methods of analytic hierarchy process (AHP) and gray target decision were used to solve the problem. Firstly, AHP and gray target decision method were introduced respectively in detail. Secondly, three automobile noise reduction schemes were illustrated. Four types of data were selected as the decision indexes, and the weight coefficients of all the decision indexes were calculated using the AHP. Then multi-attribute mixed weighted gray target decision model was established. The optimum scheme was obtained by the calculation of the off-target distance and the sorting of the calculation results. The proposed method can quantify the evaluation process and overcome the disadvantages of the traditional analogy method. The example shows that the method is feasible.

Abstract The proposed approach present the development of a computer tool that allows, in the first phase, the modeling of the electric vehicle power chain. This phase is based on a library developed under the Matlab-Simulink simulation environment. This library contains all the components of the power chain; it offers the selection of the desired configuration of each component. In the second phase, the tool solves the autonomy optimization problem. This problem is resolved by a program based on genetic algorithms. This program permits to optimize the configuration parameters maximizing the vehicle autonomy of the chosen chain. This tool is based on a graphical interface developed under the Matlab simulation environment.

Abstract The vibration behavior of components exposed to aerodynamic loads must be taken into consideration when designing aerial vehicles. Numerical simulation plays a key role in developing more realistic analytical models for panel flutter analysis. The notable feature of the present research is the use of two methods for the aeroelastic analysis of two-dimensional curved panels with cylindrical bending. In the first approach, the finite volume method (FVM) is used for supersonic viscous flow and nonlinear structural model while full Navier-Stokes equations are discretized. In the second approach, the third-order nonlinear piston theory aerodynamics in addition to mechanical and thermal loads is assumed. Moreover, the semi-analytical weighted residual method for the nonlinear curved panel is utilized. These approaches are concurrently compared with each other for the first time. Furthermore, Hamilton’s principle is used and partial differential equations (PDEs) are derived.

Abstract Future SAE Level 4 and Level 5 autonomous vehicles (AV) will require novel applications of localization, perception, control, and artificial intelligence technology in order to offer innovative and disruptive solutions to current mobility problems. This article concentrates on low-speed autonomous shuttles that are transitioning from being tested in limited traffic, dedicated routes to being deployed as SAE Level 4 automated driving vehicles in urban environments like college campuses and outdoor shopping centers within smart cities. The Ohio State University has designated a small segment in an underserved area of the campus as an initial AV pilot test route for the deployment of low-speed autonomous shuttles. This article presents initial results of ongoing work on developing solutions to the localization and perception challenges of this planned pilot deployment.