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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 The development of electric commercial vehicles brought up novel challenges in the design of efficient and reliable air brake systems. The compressor is one of the critical components of the air brake system and is responsible for supplying pressurized air to the brake system. In this study, we aimed to gather essential information regarding the pressure and flow rate requirements for the compressor in the air brake system of electric commercial vehicles. We extensively analyzed the existing air brake systems utilized in conventional commercial vehicles. We examined the performance characteristics of reciprocating compressors traditionally employed in these systems. Recognizing the need for novel compressor designs tailored to electric commercial vehicles, we focused on identifying the specifics such as efficiency, performance characteristics, reliability, and cost of the compressor.

Abstract Measurements of air–fuel ratio (AFR) and λ (AFRactual/AFRstoich) are crucial for understanding internal combustion engine (ICE) performance. However, current λ sensors suffer from long light-off times (on the order of seconds following a cold start) and limited time resolution. In this study, a four-color mid-infrared laser absorption spectroscopy (LAS) sensor was developed to provide 5 kHz measurements of temperature, CO, CO2, and NO in engine-out exhaust. This LAS sensor was then combined with 1 kHz hydrocarbon (HC) measurements from a flame ionization detector (FID), and the Spindt exhaust gas analysis method to provide 1 kHz measurements of λ. To the authors’ knowledge, this is the first time-resolved measurement of λ during engine cold starts using the full Spindt method. Three tests with various engine AFR calibrations were conducted and analyzed: (1) 10% lean, (2) stoichiometric, and (3) 10% rich.

Abstract This article presents a strategy for the virtual calibration of a large-scale model representing a self-piercing rivet (SPR) connection. The connection is formed between a stack of three AA6016-T4 aluminum sheets and one SPR. The calibration process involves material characterization, a detailed riveting process simulation, virtual joint unit tests, and the final large-scale model calibration. The virtual tests were simulated by detailed solid element FE models of the joint unit. These detailed models were validated using experimental tests, namely peeling, single-lap joint, and cross-tests. The virtual parameter calibration was compared to the experimental calibration and finally applied to component test simulations. The article contains both experiments and numerical models to characterize the mechanical behavior of the SPR connection under large deformation and failure.

Abstract This study aims to explore the wear characteristics of fused deposition modeling (FDM) printed automotive parts and techniques to improve wear performance. The surface roughness of the parts printed from this widely used additive manufacturing technology requires more attention to reduce surface roughness further and subsequently the mechanical strength of the printed geometries. The main aspect of this study is to examine the effect of process parameters and annealing on the surface roughness and the wear rate of FDM printed acrylonitrile butadiene styrene (ABS) parts to diminish the issue mentioned above. American Society for Testing and Materials (ASTM) G99 specified test specimens were fabricated for the investigations. The parameters considered in this study were nozzle temperature, infill density, printing velocity, and top/bottom pattern.

Abstract In today’s landscape, environmental protection and nature conservation have become paramount across industries, spurring the ever-increasing aspect of decarbonization. Regulatory measures in transportation have shifted focus away from combustion engines, making way for electric mobility, particularly in smaller engines. However, larger applications like ships and stationary power generation face limitations, not enabling an analogous shift to electrification. Instead, the emphasis shifted to zero-carbon fuel alternatives such as hydrogen and ammonia. In addition to minimal carbon-containing emissions due to incineration of lubricating oil, hydrogen combustion with air results in nitrogen oxide emissions, still necessitating quantification for engine operation compliance with legal regulations.

Abstract This study demonstrates the defossilized operation of a heavy-duty port-fuel-injected dual-fuel engine and highlights its potential benefits with minimal retrofitting effort. The investigation focuses on the optical characterization of the in-cylinder processes, ranging from mixture formation, ignition, and combustion, on a fully optically accessible single-cylinder research engine. The article revisits selected operating conditions in a thermodynamic configuration combined with Fourier transform infrared spectroscopy. One approach is to quickly diminish fossil fuel use by retrofitting present engines with decarbonized or defossilized alternatives. As both fuels are oxygenated, a considerable change in the overall ignition limits, air–fuel equivalence ratio, burning rate, and resistance against undesired pre-ignition or knocking is expected, with dire need of characterization.

Abstract Fossil fuel reserves are swiftly depleting when consumer demand for these fuels continues to rise. In order to meet the demand and diminish the pollution derived through conventional fuels, it is crucial to employ cleaner fuels made from substitutes such as waste biomass. Also, converting waste biomass to fuel can lower usage of landfills. There are many biomass resources that are suitable for fuel production, out of which groundnut is also a potential feedstock. Groundnut shell biomass was chosen for this study, as it is a waste leftover during shelling of groundnuts for various commercial applications. The procured groundnut shells were converted to oil using pyrolysis process and was distilled. Both the pyrolysis oil and the distilled oil were analyzed using Fourier transform infrared instrument wherein the presence of functional groups such as alcohols, amines, and carboxylic acids were identified.

Abstract Various feedstocks can be employed for biodiesel production, leading to considerable variation in composition and engine fuel characteristics. Using biodiesels originating from diverse feedstocks introduces notable variations in engine characteristics. Therefore, it is imperative to scrutinize the composition and properties of biodiesel before deployment in engines, a task facilitated by predictive models. Additionally, the international commercialization of biodiesel fuel is contingent upon stringent regulations. The traditional experimental measurement of biodiesel properties is laborious and expensive, necessitating skilled personnel. Predictive models offer an alternative approach by estimating biodiesel properties without depending on experimental measurements. This research is centered on building models that correlate mid-infrared spectra of biodiesel and critical fuel properties, encompassing kinematic viscosity, cetane number, and calorific value.

Abstract For taking counter measures in advance to prevent accidental risks, it is of significance to explore the causes and evolutionary mechanism of ship collisions. This article collects 70 ship collision accidents in Zhejiang coastal waters, where 60 cases are used for modeling while 10 cases are used for verification (testing). By analyzing influencing factors (IFs) and causal chains of accidents, a Bayesian network (BN) model with 19 causal nodes and 1 consequential node is constructed. Parameters of the BN model, namely the conditional probability tables (CPTs), are determined by mathematical statistics methods and Bayesian formulas. Regarding each testing case, the BN model’s prediction on probability of occurrence is above 80% (approaching 100% indicates the certainty of occurrence), which verifies the availability of the model. Causal analysis based on the backward reasoning process shows that H (Human error) is the main IF resulting in ship collisions.

The initial cost of battery electric vehicles (BEVs) is higher than internal combustion engine-powered vehicles (ICEVs) due to expensive batteries. Various factors affect the total cost of ownership of a vehicle. In India, consumers are concerned with a vehicle’s initial purchase cost and prefer owning an economical vehicle. The higher cost and shorter range of BEVs compared to ICEVs severely limit their penetration in the Indian market. However, government subsidies and incentives support BEVs. The total cost of ownership assessment is used to evaluate the entire cost of a vehicle to find the most economical option among different powertrains. This study compares 2W (two-wheeler) and 4W (four-wheeler) BEV’s cost vis-à-vis equivalent ICEVs in Delhi and Mumbai. The cost analysis assesses the current and future government policies to promote BEVs. Two assumed policies were applied to estimate future scenarios.

Abstract After a severe lane change, a wind gust, or another disturbance, the driver might be unable to recover the intended motion. Even though this fact is known by any driver, the scientific investigation and testing on this phenomenon is just at its very beginning, as a literature review, focusing on SAE Mobilus® database, reveals. We have used different mathematical models of car and driver for the basic description of car motion after a disturbance. Theoretical topics such as nonlinear dynamics, bifurcations, and global stability analysis had to be tackled. Since accurate mathematical models of drivers are still unavailable, a couple of driving simulators have been used to assess human driving action. Classic unstable motions such as Hopf bifurcations were found. Such bifurcations seem almost disregarded by automotive engineers, but they are very well-known by mathematicians. Other classic unstable motions that have been found are “unstable limit cycles.”

Abstract The air-breathing hypersonic vehicle (AHV) holds the potential to revolutionize global travel, enabling rapid transportation to low-Earth orbit and even space within the next few decades. This study focuses on investigating the nonlinear dynamic simulation, trim, and stability analysis of a three-degrees-of-freedom (3DOF) longitudinal model of a generic AHV for variable control surface deflection, δe and δr. A simulation is developed to analyze the burstiness of the AHV’s nonlinear longitudinal behavior, considering the complete flight envelope across a wide range of Mach numbers, from M = 0 to 24, for selected stable M. The presented simulation assesses trim analysis and explores the dynamic stability of the AHV through its flight envelope and bifurcation method analysis is carried out to gain insight and validate the dynamic stability using eigen value approach.

Abstract This article investigates the performance of a low-cost throttle-by-wire-system (TbWS) for two-wheeler applications. Mopeds/scooters are still restricted as environmentally harmful. TbWSs can contribute to environmental protection by replacing conventional restrictors. Its consisting of an anisotropic magnetoresistance (AMR) throttle position sensor and a position-controlled stepper motor-driven throttle valve actuator. The decentralized throttle position sensor is operating contactless and acquires redundant data. Throttle valve actuation is realized through a position-controlled stepper motor, sensing its position feedback by Hall effect. Using a PI controller, the stepper motor position is precisely set. Both units transmit and receive data by a CAN bus. Furthermore, fail-safe functions, plausibility checks, calibration algorithms, and energy-saving modes have been implemented.

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 In autonomous technology, uncrewed aircraft systems have already become the preferred platform for the research and development of flight control systems. Although they are subjected to following and satisfying complicated scenarios of control stations, this high dependency on a specific control framework limits them in their application process and reduces the flight self-organizing network. In this article, we present a developed multilayer control system protocol with the additional supportive manned aircraft layer (Tender). The novelty of the introduced model is that uncrewed aircraft systems are monitored and navigated by the tender, and then based on the suggested scheme, data flows are controlled and transferred across the network by the developed cloud–robotics approach in the ground station layer.

Abstract A growing interest in electromechanical brakes (EMB) is discernible in the automotive industry finding its climax in an announcement of EMB series production in late 2022 [1]. The introduction of EMB allows for new design opportunities using distributed software on smart actuators. However, additional efforts are needed to ensure continuously high levels of safety even when established design principles in the brake system are changed. This article discusses different safety concepts that could potentially be put in place in EMB actuators. Therefore, safety goals that need to be satisfied by an actuator are derived. Furthermore, three different degrees of complexity are differentiated, evolving to different required electronic control units (ECU) and architectures. Additionally, also the safety of the actuation unit (AU) is considered to realize a holistic safety concept for the actuator. Finally, a conclusion is drawn comparing the different investigated concepts.

Abstract This article presents a novel approach to optimize the placement of light detection and ranging (LiDAR) sensors in autonomous driving vehicles using machine learning. As autonomous driving technology advances, LiDAR sensors play a crucial role in providing accurate collision data for environmental perception. The proposed method employs the deep deterministic policy gradient (DDPG) algorithm, which takes the vehicle’s surface geometry as input and generates optimized 3D sensor positions with predicted high visibility. Through extensive experiments on various vehicle shapes and a rectangular cuboid, the effectiveness and adaptability of the proposed method are demonstrated. Importantly, the trained network can efficiently evaluate new vehicle shapes without the need for re-optimization, representing a significant improvement over classical methods such as genetic algorithms.

Abstract With the use of the stepped surface of the friction pairs of the stepped bearings (SB) in the high-speed centrifugal pumps, its liquid film thickness is suddenly changed and it was discontinuously distributed in the direction of motion of pump. To ensure the continuity of the liquid film thickness and enhance the lubrication efficiency of the pump, based on the lubrication model of the SB, two other structures of the inclined surfaces [inclined bearings (IB)] and curved surfaces [curved bearings (CB)] used to replace stepped surfaces of the SB are investigated, respectively. Under the same conditions of the minimum thickness of the liquid film and initial dimensions of the sliding friction pairs, the influence of both the thickness ratio (α) of the liquid film and dimension ratio (β) in the direction of motion of SB, IB, and CB on the bearing capacity and friction coefficient of the liquid film are simulated and analyzed, respectively.