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Abstract This article introduces an innovative method for predicting tire–road interaction forces by exclusively utilizing longitudinal and lateral acceleration measurements. Given that sensors directly measuring these forces are either expensive or challenging to implement in a vehicle, this approach fills a crucial gap by leveraging readily available sensor data. Through the application of a multi-output neural network architecture, the study focuses on simultaneously predicting the longitudinal, lateral, and vertical interaction forces exerted by the rear wheels, specifically those involved in traction. Experimental validation demonstrates the efficacy of the methodology in accurately forecasting tire–road interaction forces. Additionally, a thorough analysis of the input–output relationships elucidates the intricate dynamics characterizing tire–road interactions.

Abstract This article presents the design and the analysis of a control logic capable of optimizing vehicle’s energy consumption during a braking maneuver. The idea arose with the purpose of enhancing regeneration and health management in electric vehicles with electro-actuated brakes. Regenerative braking improves energy efficiency and allows a considerable reduction in secondary emissions, but its efficiency is strongly dependent on the state of charge (SoC) of the battery. In the analyzed case, a vehicle equipped with four in-wheel motors (one for each wheel), four electro-actuated brakes, and a battery was considered. The proposed control system can manage and optimize electrical and energy exchanges between the driveline’s components according to the working conditions, monitoring parameters such as SoC of the battery, brake temperature, battery temperature, motor temperature, and acts to optimize the total energy consumption.

Abstract Using ammonia as a carbon-free fuel is a promising way to reduce greenhouse gas emissions in the maritime sector. Due to the challenging fuel properties, like high autoignition temperature, high latent heat of vaporization, and low laminar flame speeds, a dual-fuel combustion process is the most promising way to use ammonia as a fuel in medium-speed engines. Currently, many experimental investigations regarding premixed and diffusive combustion are carried out. A numerical approach has been employed to simulate the complex dual-fuel combustion process to better understand the influences on the diffusive combustion of ammonia ignited by a diesel pilot. The simulation results are validated based on optical investigations conducted in a rapid compression–expansion machine (RCEM). The present work compares a tabulated chemistry simulation approach to complex chemistry-based simulations.

Abstract This article presents a technical study on the integration of hybrid renewable energy sources (RES) with vehicle-to-grid (V2G) technology, aiming to enhance energy efficiency, grid stability, and mitigating power imbalances. The growing adoption of RES and electric vehicles (EV) necessitates innovative solutions to mitigate intermittency and optimize resource utilization. The study’s primary objective is to design and analyze a hybrid distribution generation system encompassing solar photovoltaic (PV) and wind power stations, along with a conventional diesel generator, connected to the utility grid. A V2G system is strategically embedded within the microgrid to facilitate bidirectional power exchange between EV and the grid. Methodologically, MATLAB/Simulink® 2021a is employed to simulate the system’s performance over one day.

Abstract Demonstrating ring pack operation in an operating engine is very difficult, yet it is essential to optimize engine performance parameters such as blow-by, oil consumption, emissions, and wear. A significant amount of power is lost in friction between piston ring–cylinder liner interfaces if ring pack parameters are not optimized properly. Thus, along with these parameters, it is also necessary to reduce friction power loss in modern internal combustion engines as the oil film thickness formed between the piston ring and liner is vital for power loss reduction due to friction. Hence, it has also been a topic of research interest for decades. Piston and ring dynamics simulation software are used extensively for a better ring pack design. In this research work, a similar software for piston ring dynamics simulation reviews the ring pack performance of a four-cylinder diesel engine.

Abstract This article introduces a methodology for conducting comparative evaluations of vibration-induced discomfort. The aim is to outline a procedure specifically focused on assessing and comparing the discomfort caused by vibrations. The article emphasizes the metrics that can effectively quantify vibration-induced discomfort and provides insights on utilizing available information to facilitate the assessment of differences observed during the comparisons. The study also addresses the selection of appropriate target scenarios and test environments within the context of the comparative evaluation procedure. A practical case study is presented, highlighting the comparison of wheel corner concepts in the development of new vehicle architectures. Currently, the evaluation criteria and difference thresholds available allow for comparative evaluations within a limited range of vehicle vibration characteristics.

Abstract The ground vibration test (GVT) is an important phase in a new aircraft development program, or the structural modification of a certified aircraft, to experimentally determine the structural vibrational modes of the aircraft and their modal parameters. These modal parameters are used to validate and correlate the dynamic finite element model of the aircraft to predict potential structural instabilities (such as flutter), assessing the significance of modifications to research vehicles by comparing the modal data before and after the modification and helping to resolve in-flight anomalies. Due to the high cost and the extensive preparations of such tests, a new method of vibration testing called the taxi vibration test (TVT) rooted in operational modal analysis (OMA) was recently proposed and investigated as an alternative method to conventional GVT.

Abstract NVH refinement of commercial vehicles is the key attribute for customer acceptance. Engine and road irregularities are the two major factors responsible for the same. During powertrain isolators’ design alone, the mass and inertia of the powertrain are usually considered, but in practical scenarios, a directly coupled subsystem also disturbs the boundary conditions for design. Due to the upgradation in emission norms, the exhaust aftertreatment system of modern automotive vehicles becomes heavier and more complex. This system is further coupled to the powertrain through a flexible joint or fixed joint, which results in the disturbance of the performance of the isolators. Therefore, to address this, the isolators design study is done by considering a multi-body dynamics model of vehicles with 16 DOF and 22 DOF problems, which is capable to simulate static and dynamic real-life events of vehicles.

Abstract Throughout the automobile industry, the electronic brake boost technologies have been widely applied to support the expansion of the using range of the driver assist technologies. The electronic brake booster (EBB) supports to precisely operate the brakes as necessary via building up the brake pressure faster than the vacuum brake booster. Therefore, in this article a novel control strategy for the EBB based on fuzzy logic control (FLC) is developed and studied. The configuration of the EBB is established and the system model including the permanent magnet synchronous motor (PMSM), a two-stage reduction transmission (gears and a ball screw), a servo body, reaction disk, and the hydraulic load are modeled by MATLAB/Simulink. The load-dependent friction has been compensated by using Karnopp friction model. Due to the strong nonlinearity on the EBB components and the load-dependent friction, FLC has been used for the control algorithm.

Abstract Due to the presence of uncertain disturbances in the actual steering system, disturbances in the system may affect the handling stability of the vehicle. Therefore, this article proposes an integrated steering system control strategy with stronger anti-disturbance performance. When disturbances exist in the system, the proposed control strategy effectively reduces the attitude changes during the vehicle steering process. In the upper-level control strategy, a variable transmission ratio curve is designed to coordinate the high-speed handling stability and low-speed steering sensitivity of the vehicle. On this basis, a sideslip angle observer is proposed based on the extended state observation theory, which does not depend on an accurate system model, thus determining the intervention timing of the active front wheel steering system. In the lower-level control strategy, DR-PI/DR-PID controllers are designed for the integrated steering system.

Abstract To realize the dynamics concept “enjoy driving” of new-model cars, engine sound was based on the concept of “exhilarating.” To achieve “exhilarating,” we compared current models with competitor cars to understand the countermeasure sound characteristics. As a result, it was found that the rumble noise at low-RPM medium load needs to be reduced. To reduce rumble noise, the crankshaft system and power train stiffness were refined. As a result, we were able to achieve our goal of exhilarating engine sound. However, as the evaluation of sound after a vehicle is sold is generally left to the user, there are few studies that examine whether a car is more highly evaluated based on the sounds it creates. Therefore, this study was conducted to evaluate concept compatibility and loyalty in relation to exhilarating engine sound in the U.S. market for Generation Z, the target group for the new car.

Abstract A time domain analysis method of ride comfort and energy dissipation characteristics is proposed for automotive vibration proportional–integral–derivative (PID) control. A two-degrees-of-freedom single wheel model for automotive vibration control is established, and the conventional vibration response variables for ride comfort evaluation and the energy consumption vibration response variables for energy dissipation characteristics evaluation are determined, and the Routh stability criterion method was introduced to assess the impact of PID control on vehicle stability. The PID control parameters are tuned using the differential evolution algorithm, and to improve the algorithm’s adaptive ability, an adaptive operator is introduced, so that the mutation factor of differential evolution algorithm can change with the number of iterations.

Abstract The notable increase in combustion noise in the 7–10 kHz band has become an issue in the development of pre-chamber jet ignition combustion gasoline engines that aim for enhanced thermal efficiency. Combustion noise in such a high-frequency band is often an issue in diesel engine development and is known to be due to resonance in the combustion chamber. However, there are few cases of it becoming a serious issue in gasoline engines, and effective countermeasures have not been established. The authors therefore decided to elucidate the mechanism of high-frequency combustion noise generation specific to this engine, and to investigate effective countermeasures. As the first step, in order to analyze the combustion chamber resonance modes of this engine in detail, calculation analysis using a finite element model and experimental modal analysis using an acoustic excitation speaker were conducted.

Abstract An automatic collision avoidance control method integrating optimal four-wheel steering (4WS) and direct yaw-moment control (DYC) for autonomous vehicles on curved road is proposed in this study. Optimal four-wheel steering is used to track a predetermined trajectory, and DYC is adopted for vehicle stability. Two single lane change collision avoidance scenarios, i.e., a stationary obstacle in front and a moving obstacle at a lower speed in the same lane, are constructed to verify the proposed control method. The main contributions of this article include (1) a quintic polynomial lane change trajectory for collision avoidance on curved road is proposed and (2) four different kinds of control method for autonomous collision avoidance, namely 2WS, 2WS+DYC, 4WS, and 4WS+DYC, are compared. In the design of DYC controller, two different feedback control methods are adopted for comparison, i.e., sideslip angle feedback and yaw rate feedback.

Abstract In order to enhance the path-tracking accuracy and adaptability of the electric flatbed vehicle (EFV) in the soft-target vehicle test system, an improved controller is designed based on the linear quadratic regulator (LQR) algorithm. First, the LQR feedback controller is designed based on the EFV dynamics tracking error model, and the genetic algorithm is utilized to obtain the optimal weight coefficient matrix for different speeds. Second, a weight coefficient matrix compensation strategy is proposed to address the changes in the relationship between the vehicle–road position and attitude caused by external disturbances and the state of EFV. An offline parameter table is created to reduce the computational load on the microcontroller of EFV and enhance real-time path-tracking performance. Furthermore, an adaptive preview time control strategy is added to reduce the overshooting caused by control delay. This strategy is based on road curvature and traveling speed.

Abstract A unique torque converter test setup was used to measure the torque transmissibility frequency response function of four torque converter clutch dampers using a stepped, multi-sine-tone, excitation technique. The four torque converter clutch dampers were modeled using a lumped parameter technique, and the damper parameters of stiffness, damping, and friction were estimated using a manual, iterative parameter estimation process. The final damper parameters were selected such that the natural frequency and damping ratio of the simulated torque transmissibility frequency response functions were within 10% and 20% error, respectively, of the experimental modal parameters. This target was achieved for all but one of the tested dampers. The damper models include stiffness nonlinearities, and a speed-dependent friction torque due to centrifugal loading of the damper springs.

Abstract This scientific publication presents the application of artificial intelligence (AI) techniques as a virtual sensor for tailpipe emissions of CO, NOx, and HC in a high-performance vehicle. The study aims to address critical challenges faced in real industrial applications, including signal alignment and signal dynamics management. A comprehensive pre-processing pipeline is proposed to tackle these issues, and a light gradient-boosting machine (LightGBM) model is employed to estimate emissions during real driving cycles. The research compares two modeling approaches: one involving a unique “direct model” and another using a “two-stage model” which leverages distinct models for the engine and the aftertreatment. The findings suggest that the direct model strikes the best balance between simplicity and accuracy.

Abstract Accurate estimation of traction force is essential for the development of advanced control systems, particularly in the domain of autonomous driving. This study presents an innovative approach to enhance the estimation of tire–road interaction forces under combined slip conditions, employing a combination of empirical models and neural networks. Initially, the well-known Pacejka formula, or magic formula, was adopted to estimate tire–road interaction forces under pure longitudinal slip conditions. However, it was observed that this formula yielded unsatisfactory results under non-pure slip conditions, such as during curves. To address this challenge, a neural network architecture was developed to predict the estimation error associated with the Pacejka formula. Two distinct neural networks were developed. The first neural network employed, as inputs, both longitudinal slip ratios of the driving wheels and the slip angles of the driving wheels.

Abstract In this study, a novel assessment approach of in-vehicle speech intelligibility is presented using psychometric curves. Speech recognition performance scores were modeled at an individual listener level for a set of speech recognition data previously collected under a variety of in-vehicle listening scenarios. The model coupled an objective metric of binaural speech intelligibility (i.e., the acoustic factors) with a psychometric curve indicating the listener’s speech recognition efficiency (i.e., the listener factors). In separate analyses, two objective metrics were used with one designed to capture spatial release from masking and the other designed to capture binaural loudness. The proposed approach is in contrast to the traditional approach of relying on the speech recognition threshold, the speech level at 50% recognition performance averaged across listeners, as the metric for in-vehicle speech intelligibility.

Abstract Ground vibration testing (GVT) is an important phase of the development, or the structural modification of an aircraft program. The modes of vibration and their associated parameters extracted from the GVT are used to modify the structural model of the aircraft to make more reliable dynamics predictions to satisfy certification authorities. Due to the high cost and the extensive preparations for such tests, a new method of vibration testing called taxi vibration testing (TVT) rooted in operational modal analysis (OMA) was recently proposed and investigated by the German Institute for Aerospace Research (DLR) as alternative to conventional GVT. In this investigation, a computational framework based on fully coupled flexible multibody dynamics for TVT is presented to further investigate the applicability of the TVT to flexible airframes. The time domain decomposition (TDD) method for OMA was used to postprocess the response of the airframe during a TVT.