Engineering

Abstract: To comprehensively improve vehicle ride comfort and handling stability, as well as to enhance the robustness and disturbance rejection capability of the suspension system under uncertain operating conditions, this paper first establishes a full vehicle suspension dynamic model. On this basis, an improved SH-ADD controlled suspension is proposed as a reference model through the analysis of power flow characteristics within the suspension system, and a sliding mode control (SMC) strategy is subsequently designed based on this reference model. Simulation results indicate that, compared with conventional control strategies, the proposed algorithm offers a clear advantage in reducing the root mean square (RMS) values of sprung mass acceleration, thereby effectively suppressing body vibration and improving ride comfort. In addition, both roll and pitch angular accelerations are notably reduced, contributing to enhanced body attitude stability. Moreover, when subjected to parameter uncertainties such as variations in vehicle speed and sprung mass, the proposed controller maintains excellent robustness and stable control performance, demonstrating its overall effectiveness in improving suspension system performance under complex operating conditions.

Abstract: Modern vehicles carry front and rear radar, forward and surround-view cameras, and increasingly infrared sensing as standard driver-assistance equipment. This paper investigates whether that same sensor suite, fused and fed forward into the suspension control loop, can measurably improve ride quality on unpaved and off-road surfaces, for both the vehicle chassis and, as a secondary actuation layer, the occupant seat. We formalize a sensor-fusion, road/suspension estimation, control, and feedback architecture into a state-space model; derive the governing equations for a three-degree-of-freedom quarter-car-plus-seat plant; specify a multi-sensor preview measurement model and an inverse-variance fusion law; design and compare passive, reactive, and predictive controllers; and implement and evaluate the full pipeline in Python on a synthetic ISO 8608 [2] off-road profile with embedded speed-bump test events. The predictive controller reduces ISO 2631-weighted [1] body (chassis) RMS acceleration by 23.7% and seat/occupant RMS acceleration by 67.9% relative to a passive baseline. We further replace two hand-engineered blocks with learned counterparts — a neural network that corrects context-dependent sensor bias, and a Random Forest terrain classifier that drives gain scheduling — and report the resulting, honestly modest, additional gains. A prior-art survey spanning patents [4–7,10,11] and production systems [8,9], and a review of public datasets [12–14,18] suitable for validating this class of system, precede an explicit novelty and freedom-to-operate discussion.

Abstract: Risk-based prioritization frameworks such as the Intelligent Pedestrian Model (IPM) rank pedestrians by an instantaneous, reference-normalized risk score. They indicate which pedestrian requires attention first. This study examines the temporal stability of such rankings. We computed an observation-only kinematic Exposure proxy frame by frame on three ETH/UCY benchmark scenes. In these scenes, the highest-priority identity changes rapidly: the median top-1 persistence is two frames (0.8 s). We introduce a switch classification that separates established switches from entry-driven and forced switches. Grace-period exclusion is evaluated as a sensitivity variant and shown to remove up to 82% of evaluable time in short-track scenes. Established flicker rates range from one switch per 2.7 s in dense scenes to one per 25.4 s in sparse scenes, with switches concentrated at small top-1–top-2 risk gaps. The results show that instantaneous rankings alone may be insufficient for sustained attention allocation and motivate future work on temporal priority management.

Abstract: Adaptive cruise control (ACC) and related advanced driver assistance systems (ADAS) regulate vehicle speed mainly for safety and comfort. In a battery electric vehicle (BEV), the same speed decisions also determine energy use, and therefore range. This concept paper couples the two concerns: a predictive longitudinal controller is developed, from first principles and without empirical validation, that plans ADAS speed and manages BEV energy within a single problem. The vehicle longitudinal dynamics, the powertrain efficiency map, and the regenerative brake-blending limits are embedded in a model predictive control (MPC) formulation whose cost function weighs gap-keeping safety, ride comfort, and battery energy over a receding horizon, informed by electronic-horizon (map and traffic) preview. To make the controller deployable, the safety-critical deceleration path is separated from the energy-optimization layer; this separation is supported by a worked hazard analysis (HARA) and by the derived ISO 26262 safety goals. A first-principles calculation shows that keeping a deceleration within the regeneration power limit recovers substantially more energy than late, hard braking. No simulation or vehicle data are reported: the contributions are the formulation, the safety architecture, and a concrete evaluation protocol, with its main threats to validity, to guide the quantitative study that should follow.

Abstract: Public run-to-failure datasets support transparent condition monitoring, but the sensitivity of simple vibration features to analysis choices is rarely reported. This study presents a reproducible raw-signal-to-result workflow for 20 MATLAB files from the public University of New South Wales spur-gear wear dataset. Feature sensitivity is evaluated for spectral window, record length, Welch segment length, sideband order, local harmonic-band width, and small speed-reference biases; a Hilbert-envelope spectrum provides a selective demodulation baseline. In the dry sequence, both vibration-channel root-mean-square values increased more than threefold, and the second gear-mesh harmonic increased by a factor of 3.53. In the lubricated sequence, global RMS changed weakly, whereas the 2–13 kHz and 20–37 kHz band-RMS measures and first-harmonic sideband index had Spearman correlations of 0.782, 0.758, and 0.830. Broad-band RMS trends remained positive across all tested windows, record lengths, and Welch settings. Exact-bin harmonics were sensitive to speed-reference bias, whereas a ±5 Hz local-band RMS retained the dry second-harmonic correlation of 0.842 over ±0.1% bias. The lubricated 2–13 kHz envelope first-order index was strongly negative (ρ = −0.782), indicating complementary rather than consistently superior behavior. The contribution is a reproducible parameter-robustness map and practical guidance for selecting interpretable first-level gear-wear indicators.

Abstract: Pedestrian-detection research and vehicle-safety assessment have traditionally concentrated on upright, walking or crossing pedestrians. People who are prone, supine, lateral, seated, crouched, kneeling, partially collapsed or undergoing a fall present different visual, geometric, thermal and kinematic characteristics. These differences can reduce transferability from conventional benchmarks and make apparently similar studies difficult to compare when posture definitions, data provenance, environmental conditions, latency accounting and safety assumptions are reported inconsistently. This article proposes NUP-REPORT 1.0, a minimum reporting and benchmarking framework for non-upright pedestrian detection and pre-crash safety evaluation. The framework was developed through a structured narrative synthesis of five evidence streams: epidemiology of pedestrians lying on the road; pedestrian and multispectral detection benchmarks; uncertainty and calibration methods; scenario-based automated-driving evaluation; and current public safety standards and assessment protocols. A failure-chain decomposition was then used to define six reporting domains: target and posture; scenario and environment; sensors and data provenance; model and fusion architecture; performance and uncertainty; and vehicle-level safety interpretation. NUP-REPORT further proposes a minimum scenario matrix, a core outcome set, explicit timing definitions, stopping-margin equations and a 30-item checklist. The framework distinguishes object-detection accuracy from safety-relevant performance by requiring posture-stratified outcomes, time-to-first-detection, end-to-end latency, confidence calibration, sensor-degradation sensitivity, safety-critical false negatives and transparent vehicle-response assumptions. NUP-REPORT is not a regulatory test protocol, consensus standard or performance threshold. It is a versioned reporting proposal intended to improve interpretability, reproducibility and comparability while supporting future dataset development, inter-laboratory validation and standards engagement.

Abstract: This simulation-based case study investigates vehicle handling performance during severe asymmetric and symmetric tire inflation pressure loss, comparing self-supporting run-flat tires (SSRFT) to conventional radial configurations. To capture the complex coupled interactions occurring under severe pressure depletion, this work introduces a non-linear 9-Degree-of-Freedom (9-DOF) multi-body dynamics numerical simulation framework parameterized to an F56 MINI Cooper S platform. The mathematical plant model expands upon classical planar approximations by fully integrating dynamic chassis roll, pitch, and four independent wheel spin rotational degrees of freedom. The core tire-road interface is parameterized using empirical constants parsed from a proprietary Michelin Magic Formula 6.2 (.tir) baseline data file acquired through manufacturer collaboration. Because physical test-rig boundaries prohibit zero-pressure execution, unpressurized (0 kPa) carcass-only structural degradation profiles and sidewall stiffness retention indices are formulated based on hyperelastic limits from literature. To eliminate human driver variability and bypass the limitations of open-loop steering inputs, path tracking is governed by a closed-loop, two-point preview Stanley steering control algorithm. The vehicle model is subjected to the strict spatial corridor constraints of an unthrottled ISO 3888-2 double-lane change maneuver at an entry speed of 80 km/h under an unthrottled inertial speed decay regime. To map the true limits of structural failures, three distinct puncture topologies are evaluated sequentially: asymmetric Front-Left (FL) deflation, asymmetric Front-Right (FR) deflation, and symmetric dual front-axle deflation. A complete parametric sensitivity analysis is performed on the primary tracking gains to isolate structural tire behavior from the guidance loop. Quantitative model-based observations demonstrate that while conventional radial plies enter rapid understeer saturation and continuous contact patch sliding, the structural sidewall insert rubber (SIR) of the SSRFT maintains stable handling margins and minimizes lateral track errors. These quantified performance variations provide baseline metrics to inform virtual vehicle prototyping and parametric chassis control tuning.

Abstract: This paper presents a compact microstrip patch antenna operating at 5.9 GHz with enhanced bandwidth and reduced cross-polarization levels. The proposed design employs a single edge-notch technique to achieve bandwidth doubling compared to the conventional patch antenna. However, this modification introduces elevated cross-polarization levels across the operating band. To address this issue, two symmetric cuts are introduced in the ground plane, significantly suppressing cross-polarization while maintaining the extended bandwidth. The antenna is designed and simulated using MATLAB Antenna Toolbox, with comprehensive analysis of VSWR, impedance bandwidth, radiation patterns, gain, and directivity characteristics. With an impedance bandwidth exceeding 800 MHz, the final design is well-suited for Vehicle-to-Everything (V2X) communications, Industrial, Scientific, and Medical (ISM) band applications, and unmanned aerial vehicle (UAV) systems—all of which require a compact form factor and stable radiation characteristics. The proposed antenna demonstrates improved performance with H-plane cross-polarization levels reduced by 8.5–23 dB (depending on frequency) compared to the edge-notched configuration without ground modifications, while maintaining a compact footprint.

Abstract: Fallen pedestrians—those lying prone, supine, or crouching on roadways—represent a critical and under-addressed vulnerability in contemporary Advanced Driver Assistance Systems (ADAS). In simulation, a baseline RGB camera system achieved a 21.4% true-positive detection rate (TPR) at night for non-upright subjects, compared with a simulated 98.2% TPR achieved by the Advanced Fallen Object Detection System (AFODS) under the same night-time (0 lux) condition—a 76.8 percentage-point simulated detection gap. This article synthesises three complementary peer-reviewed studies into a proposed closed-loop safety architecture: (1) simulation-based multi-modal detection via AFODS; (2) a physics-grounded design evaluated through simulation for post-collision kinematic reconstruction; and (3) simulation-based injury-risk quantification translating detection latency into Head Injury Criterion (HIC) and AIS-graded fatality probability. The integrated framework is associated with Japanese Patent Application No. 2025-167440, filed on 3 October 2025, and JST support has been approved for the planned PCT filing and further development of the detection and information-processing claims. In the source simulation, modelled fatal head-injury probability at 50 km/h falls from 66.2% (no-detection baseline) to 0.7% under worst-case AFODS-triggered braking—a 65.5-percentage-point model-chain contrast that has not yet been empirically observed. A five-stage validation roadmap is proposed, targeting eventual conformance assessment against ISO 26262, ISO 21448 (SOTIF), and relevant NCAP protocols. The article identifies open research challenges and a proposed trajectory toward prototype testing; it does not report empirical validation, legal admissibility findings, or deployment, all of which remain future work.

Abstract: The first paper in this series treated Blind Spot Detection (BSD) as a radar-only automotive perception function. This follow-up study asks whether a camera-based (CNN object-detector) BSD pipeline can match a radar-based one, and what sensor fusion adds, using a literature-grounded comparative simulation rather than an opinion. A radar pipeline (FMCW range-Doppler, illumination-invariant detection) and a camera pipeline (detection probability parametrized from published day/night object-detection accuracy ratios on the BDD100K benchmark) are evaluated against an identical ground-truth overtaking scenario across three illumination conditions, using a 2,000-trial Monte Carlo framework. Results show radar consistently outperforms camera on detection latency (20 ms vs. 35–54 ms) and false-alert rate (0.7–0.9% vs. 1.85–4.75%, worsening as lighting degrades), while missed-detection rate is statistically indistinguishable between sensors under ordinary overtaking dynamics — a result that only diverges under aggressive closing speeds above roughly 18–20 m/s combined with degraded illumination. Classical OR/AND sensor-fusion rules are shown to trade latency against false-alert rate rather than improving both simultaneously. A qualitative validation section runs a real pretrained detector (YOLOv8n) against public dashcam video, reproducing the same zone-occupancy alert logic on real detections and surfacing a real, brief detection dropout consistent with the simulation's stochastic detection model. All code, figures, and results are openly reproducible and archived alongside this paper.

Abstract: The paper aims to explain in the simplest possible way how tyres influence, to the greatest extent, the dynamic behaviour of cars, i.e. vehicle handling, during power-on or power-off. Starting from the ISO 4138 steering pad test, controlled power-on and power-off manoeuvres are introduced to reproduce typical manoeuvres relevant for active safety. Handling diagrams are used to make clear how tyres determine the oversteer and understeer character of a car. A simple two degrees-of-freedom analytical vehicle model and a complex high-fidelity fourteen degrees-of-freedom model have been used. Driver-in-the-Loop simulations were performed at a dynamic driving simulator. The study considers three representative driveline configurations, namely front-wheel drive (FWD), rear-wheel drive (RWD), and all-wheel drive (AWD). A key outcome of the study is that the fundamental mechanisms governing understeer and oversteer behaviour can be effectively captured using a simple two degrees-of-freedom model combined with appropriate tyre characteristics. The results show that the handling diagrams are a proper tool to describe handling manoeuvres during power-on or power-off. Variations in understeer and oversteer behaviour induced by power modulation can be interpreted as a direct consequence of tyre characteristics. The findings of this work highlight the pivotal role of the tyre in vehicle dynamics and active safety.

Abstract: Electric-vehicle (EV) gearboxes operate under low acoustic masking and high rotational speeds, making tonal noise and unit-to-unit NVH scatter especially relevant. However, many gearbox noise, vibration, and harshness (NVH) simulations still rely on nominal geometry, ideal assembly conditions, and simplified supports. Such models are useful for early design, but they are often insufficient for explaining the behavior of manufactured and assembled EV drive units. This structured narrative review develops a simula-tion-ready parameter framework that links manufacturing measurements, assembly data, operating conditions, and degradation indicators to numerical representations used in loaded tooth contact analysis, multibody dynamics, finite element structural models, and vibroacoustic simulation. Unlike component-centered reviews, the proposed framework classifies parameters simultaneously by physical origin and by their role in the excita-tion-transfer-radiation chain. It also introduces four simulation-readiness lev-els—nominal, tolerance-based, measurement-based, and variability-aware—and priori-tizes inputs as baseline, recommended, or advanced. Particular attention is given to gear microgeometry and flank deviations, pitch error, runout, flank waviness, bearing preload and stiffness, assembly misalignment, housing variability, motor-side excitation, temper-ature, lubrication, and wear. An illustrative EV gearbox implementation scenario demon-strates how the framework can be used to progress from concept-level prediction to pro-duction-scatter analysis. The resulting structure provides a common data-request and model-building guideline for EV powertrain development, validation, root-cause analysis, and data-driven NVH modeling.

Abstract: Autonomous driving systems often exhibit trajectory tracking behavior that differs markedly from human drivers, a phenomenon intuitively described as "mechanicalness.'' This study moves beyond the traditional focus on tracking accuracy to systematically analyze these behavioral differences through a real-vehicle comparative experiment. Using a steer-by-wire vehicle equipped with the open-source Autoware platform, trajectory data were collected on a closed campus road under straight and curved conditions. A five-dimensional evaluation framework is established to quantify control continuity, prediction horizon, error response mode, style adaptability, and interaction friendliness. Results show that Autoware exhibits a "high-precision, low-smoothness, zero-tolerance'' mechanical style, characterized by high-frequency micro-corrections, reactive curve entry, rigid speed tracking, and segmented braking. Human drivers, in contrast, employ an organic mode with discrete corrections, elastic path tolerance, and anticipatory coordination. The technical origins of mechanicalness are identified as four algorithmic paradigms: geometric tracking, decoupled control, error-driven logic, and limited prediction horizon. The findings further reveal a systematic safety-comfort trade-off inherent to mechanical control, and suggest optimization directions including adaptive dead-zone mechanisms, extended prediction horizons, and lateral-longitudinal coordination. These insights provide theoretical and engineering foundations for developing more human-like autonomous driving control strategies.

Abstract: Ammonia, as a hydrogen carrier and carbon-free alternative fuel, shows great potential in future low-carbon energy systems. This study uses dimethyl ether (DME) as a combustion promoter for ammonia to enhance the combustion performance of ammonia-fueled engines. To address the issue of unburned ammonia emissions, the original combustion chamber geometry was optimized by removing the squish area to enhance flame propagation. At an ammonia energy ratio (AER) of 60%, the modified combustion chamber (MCC) reduces unburned ammonia (uNH3) emissions by up to 85.46% and improves indicated thermal efficiency (ITE) by 1.93% compared to the original combustion chamber (OCC). Furthermore, to achieve higher thermal efficiency and lower pollutant emissions, the DME injection strategy was redesigned based on the MCC. The results show that adjusting the single injection timing (SIT) and injection angle (INA) of DME can effectively improve the homogeneity of the in-cylinder combustible mixture and enhance combustion efficiency; however, overly concentrated injection can lead to rapid heat release and increase the risk of knock. The split injection strategy enables more controllable combustion phasing, significantly reduces the maximum pressure rise rate (MPRR) and ringing intensity (RI), and mitigates knocking tendency. When the main injection timing (MIT) is −5 °CA ATDC, pilot injection timing (PIT) is −30 °CA ATDC, and the pilot injection ratio (PIR) is 60%, the ITE reaches 49.98%, which is 3.53% higher than that of the pure diesel mode. Greenhouse gas (GHG) and NOx emissions are reduced by 45.94% and 62.49%, respectively, with uNH3 emissions as low as 4.16 g/kw·h.

Abstract: Electric-vehicle gearboxes require simulation procedures that connect gear-mesh excitation to shaft and bearing dynamics, housing vibration, and airborne sound radiation without losing the traceability of manufacturing, assembly, and operating inputs. This paper presents a reproducible workflow for implementing that chain in COMSOL Multiphysics 6.4. The methodology combines the Multibody Dynamics or Rotordynamics Module with the Structural Mechanics and Acoustics Modules, while the CAD Import Module and Application Builder support geometry preparation and repeatable execution. A reduced-order branch uses beam rotors, equivalent bearing properties, gear-pair elements, and component-mode-synthesized flexible structures for efficient screening; a higher-fidelity branch uses three-dimensional rotors, flexible housing components, detailed bearing-foundation coupling, and acoustic radiation by finite or boundary elements. External tooth-contact analysis and measurement data are introduced through angle-dependent transmission-error, mesh-stiffness, damping, and equivalent-excitation functions. A transparent four-degree-of-freedom benchmark is included as an independent verification target for the COMSOL implementation. For a 23-tooth pinion at 3000 rpm, the gear-mesh frequency is 1150 Hz, close to the second benchmark mode at 1163.3 Hz. The calculated equivalent receiver level is 71.95 dB at the nominal point and reaches 73.63 dB at 3035 rpm. Three-mode superposition reproduces the direct panel response within 0.003% at the nominal mesh order. A 3000-sample variability propagation gives a median of 68.46 dB and a 95% interval of 59.76-75.56 dB, demonstrating that resonance detuning can dominate nominal excitation changes. The framework separates documented COMSOL capabilities from quantities that must be generated externally, including measured tooth-flank topography and tooth-resolved deviations, and provides a complete implementation, verification, and reporting protocol for gearbox NVH research.

Abstract: The goal of the present work is to develop accurate path algorithm and develop software for navigation of mobile robot to reach target point from the starting point avoiding obstacles on the workspace using ultrasonic sensory feedback. After location of obstacles on the workspace is determined by ultrasonic sensor, the Activity Bot will move towards the destination from the starting position. The analyses, techniques and algorithms described in the work are related to any mobile robot, and the program development and experiments described in the work and run by Simple IDE software.

Abstract: Reduced air density at altitude challenges spark-ignition combustion in light-duty vehicles, particularly in Andean countries where fleets operate between sea level and over 4000~m~a.s.l. We quantified the effect of altitude on gasoline combustion efficiency and pollutant formation using 94,263 second-by-second records (2021–2025) from ten Euro~2–5 vehicles travelling Andean and coastal corridors in Ecuador (0--4000~m~a.s.l.). Emissions were measured with a Brain Bee AGS-688 analyser with pressure compensation; fuel consumption via OBD-II; operational demand via smoothed Vehicle Specific Power (\(\mathrm{PSV_{m10}}\)) in six K-Means clusters. We propose \(R_{\mathrm{CO}}=[\mathrm{CO}]/[\mathrm{CO_2}]\) and \(R_{\mathrm{HC}}=[\mathrm{HC}]/[\mathrm{CO_2}]\) as standardised, displacement-independent combustion quality indicators. \(R_{\mathrm{CO}}\) at 3500--4000~m exceeded the 500--1000~m value by 7.5\(\times\), and \(R_{\mathrm{HC}}\) by 18\(\times\). Nitric oxide showed a non-linear ``N''-pattern, peaking locally at 2000–2500~m (212~ppm) and absolutely at 3500–4000~m (613~ppm), linked to EGR suppression and rising chamber temperature. CO emission factors reached 6.42~g/km at 2000--2500~m versus 1.32~g/km at the coast (4.9\(\times\)). These results provide the first naturalistic evidence base for calibrating high-altitude emission inventories in Andean corridors.

Abstract: The paper deals with a horizontal seat suspension system in which an electric motor is used as the force actuator. Its active system can operate in a motoring mode, but is also able to act as a generator in regenerative braking mode when the kinetic vibration energy is partially converted into electrical energy. Such an innovative approach to seat vibration control allows to improve the vibro-isolation properties of a suspension system together with reducing the energy consumption of a motor. Within the scope of this paper the effectiveness of an energy regeneration process under random vibration of various intensity is investigated experimentally. The presented results concern both the reduction of vibrations affecting the human body in sitting position, as well as the amount of energy recovered from the seat suspension system during its oscillatory motion.

Abstract: The rapid development of electric vehicles has increased the need for a better understanding of the relationships between vehicle dynamics, energy consumption and control strategies. This study presents an experimental investigation of the acceleration and coasting characteristics of a 2024 Kia Niro EV. Road tests were combined with laboratory measurements of the vehicle mass properties, including the centre of gravity. Vehicle motion parameters were recorded using a GNSS/INS measurement system, while electric powertrain data were acquired from the vehicle CAN bus using proprietary software developed by the authors. The influence of driving mode, accelerator pedal position and regenerative braking intensity was analysed. The results showed that the selected driving mode significantly affects the acceleration characteristics only at intermediate accelerator pedal positions, whereas identical maximum performance is obtained with the accelerator pedal fully depressed. The energy required to accelerate the vehicle to 90 km/h remained nearly constant under most operating conditions, indicating high electric powertrain efficiency. During coasting, regenerative braking recovered up to 50% of the energy previously required for acceleration. The obtained results provide valuable experimental data for the validation of vehicle dynamics and energy consumption models and support the development of more efficient electric vehicle control strategies.

Abstract: The hydroforming performance of trailing arms is governed by the coupled effects of feed parameters, pressure schedules and frictional characteristics. Improper parameter matching readily induces typical forming defects such as wrinkling, cracking and uneven wall thickness. To address this issue, a multi-objective optimization method for hydroforming is proposed in this study. Taking the maximum wall thickness, minimum wall thickness and die-to-workpiece gap of the tubular blank as optimization objectives, and the internal pressure and right-side axial feed velocity as design variables, an integrated numerical simulation framework combining the Archive-based Micro Genetic Algorithm (AMGA) and LS-DYNA is established to analyze the hydroforming process. By adaptively adjusting the key control points of internal pressure and axial feed loading curves, the developed method expands the solution space and realizes the automatic optimization of loading paths. The results reveal that the maximum wall thickness reduction rate of the tubular component is reduced from 20.4% to 14.8%. Meanwhile, the wall thickness uniformity is improved and forming defects are effectively suppressed while the thickening rate remains stable. Moreover, multiple sets of Pareto optimal solutions can be obtained in a single calculation. This work provides new insight into the process optimization for forming similar structural components.