Search Results (111)

Electric vehicle (EV) adoption in South Africa remains constrained by high upfront purchase costs, limited charging infrastructure, and policy uncertainty, creating a need for lower-cost and locally relevant pathways to transport decarbonisation. This study evaluates the feasibility of converting a legacy light commercial pickup platform from internal combustion engine (ICE) propulsion to battery-electric propulsion through integrated component sizing, longitudinal vehicle simulation, and techno-economic assessment. A retrofit architecture comprising a traction battery, inverter-controller, electric motor, and DC-DC converter was developed using first-principles vehicle dynamics and energy-demand analysis. The resulting configuration employed a 40 kW AC induction motor, an approximately 28 kWh battery pack, a 40–60 kW inverter with 60 kW peak capability, and a 0.75–1.2 kW auxiliary DC-DC converter. Simulation over a representative 1000 s drive cycle showed stable speed tracking, sustained vehicle motion over approximately 10 km, and peak battery currents exceeding 300 A during acceleration, while regenerative braking reduced net cumulative energy consumption relative to gross demand. The economic analysis indicated that the retrofit pathway yielded the lowest cumulative total cost of ownership over most of a 10-year horizon, with breakeven relative to the used ICE baseline occurring at approximately 3.4 years. Lifecycle analysis further showed that the retrofit configuration achieved the lowest combined production and operational carbon burden among the compared vehicle pathways. These findings indicate that ICE-to-EV retrofitting of legacy light commercial vehicles can provide a technically feasible, economically competitive, and environmentally advantageous electrification strategy for South Africa and comparable emerging markets. Full article

This study introduces a physics-informed machine learning framework for predicting transient emissions and energy variables in a retrofitted heavy-duty diesel vehicle. It merges data-driven modeling with physically derived features for reliable real-world analysis. A Random Forest regressor is trained on a public dataset (26 trips from one instrumented vehicle) to predict CO₂ and NO_x mass rates, exhaust temperature, exhaust mass flow rate, and fuel flow rate from synchronized multi-sensor inputs using past-only, time-lagged features. On held-out trips, exhaust temperature prediction achieves $R^2$ = 0.9997 and $\mathrm{RMSE}$ = 0.53 g/s; for CO₂, with $R^2$ = 0.9985 and $\mathrm{RMSE}$= 0.38 g/s, comparable performance is reported for NO_x, exhaust flow, and fuel rate. The trained model is integrated into a simulation framework to enable the evaluation of alternative operating conditions and powertrain configurations. First, the impact of cold-start versus hot-start operation is assessed, showing cumulative emission penalties of up to +28% for CO₂ and +30% for NO_x. Second, the effect of hybridization is investigated by comparing the baseline thermal configuration with a hybrid electric architecture, resulting in estimated reductions of −12.2% in CO₂ and −10.5% in NO_x emissions. This tool excels in high-fidelity emission prediction and system-level energy analysis, aiding advanced powertrain assessments under realistic driving conditions. Full article

The growing demand for energy-efficient buildings and the urgent need to retrofit aging infrastructure have driven increased interest in advanced diagnostic technologies. Among these, unmanned aerial vehicle (UAV)-based infrared thermography (IRT) has emerged as a promising non-destructive technique for assessing the thermal performance of building envelopes. This review examines recent developments and applications of dynamic infrared thermography (IRT) in the building sector for both qualitative and quantitative thermal assessment, based on previously conducted studies. It highlights the increasing adoption of integrated UAV-based IRT for building inspection and diagnostics, and critically reviews the operational, technical, and methodological advancements in dynamic thermography achieved over the past decade. Furthermore, the review presents a comprehensive framework for operational planning, encompassing environmental conditions, infrared camera configuration, and optimal UAV flight parameters. The key findings identify major challenges associated with dynamic IRT applications, particularly those related to measurement accuracy that currently limit its use for quantitative assessments and synthesize proposed methodologies to address these limitations. The review also highlights the absence of standardized procedures for determining emissivity and reflected apparent temperature in dynamic measurement setups and discusses potential approaches to overcome these gaps. Finally, it outlines priority directions for future research to support the reliable and consistent application of dynamic IRT in quantitative analysis and provides a reference for energy auditors and thermography practitioners to inform the selection of appropriate procedures for accurately quantifying heat loss in building envelopes. Full article

The decarbonization of the transportation sector necessitates the adoption of practical measures that can be implemented within existing fleets. One such measure is the installation of solar panels on trucks, which has shown potential to reduce fuel consumption in heavy-duty vehicles (HDVs). This study presents lessons learned from a monitoring project involving 200 commercial trucks retrofitted with 300–500 W solar panels, aimed at supplementing battery charging and minimizing alternator operation. The system incorporated commercially available flexible photovoltaic (PV) modules, adhesive mounting techniques, a charge controller, and a data logger housed within a control box. Documentation covered installation procedures, wiring practices, and safety considerations across various truck models, with additional insights from electrical contractors regarding labor time and costs. Results indicate that adhesive-based mounting can be carried out safely and reliably without structural modifications, although wiring and control box placement constitute the most significant portions of the installation process. The project further identified variability in installation duration and economic viability, depending on vehicle configuration and technician expertise. Overall, the findings affirm that vehicle-integrated photovoltaic (VIPV) retrofits are both technically feasible and operationally robust. They also underscore the practical requirements, constraints, and workforce considerations essential for scaling deployment within commercial fleets. Full article

This article investigates the feasibility of hydrogen-based retrofitting solutions for light commercial vehicles operating in urban freight transport. The analysis is based on a mission-driven methodology applied to a representative urban case study in the city of Rome, using synthetic route profiles and vehicle specifications derived from manufacturer datasheets. Three representative urban delivery missions are defined, characterised by cumulative daily distances of approximately 190–200 km and associated energy requirements in the range of 54–57 kWh. These mission profiles are first used to assess a commercially representative battery electric vehicle configuration, for which the usable onboard battery energy is estimated at 41.6 kWh. The results show that, under the considered operating conditions, the battery electric configuration is not able to complete the planned routes without intermediate recharging. On this basis, a fuel cell hybrid electric vehicle retrofit configuration is evaluated, combining a 35 kWh battery, a 45 kW fuel cell system and 3.5 kg of onboard hydrogen storage at 350 bar. The resulting estimated driving range is approximately 293 km, which is sufficient to satisfy the defined mission requirements. This study is framed as a technical feasibility assessment and does not aim to provide optimisation or experimental validation. The proposed methodology can be applied to other urban contexts by adapting route characteristics and daily mileage requirements. Full article

Urban rail transit networks in developing countries are rapidly expanding, entering a networked operational phase where accurate passenger flow forecasting is crucial for optimizing vehicle scheduling, resource allocation, and transportation efficiency. In the short term, accurate real-time forecasting enables the dynamic adjustment of train headways and crew deployment, reducing average passenger waiting times during peak hours and alleviating platform overcrowding; in the long term, reliable trend predictions support strategic planning, including capacity expansion, station retrofitting, and energy management. This paper proposes a novel hybrid forecasting model, EEMD-TiDE, that combines improved Ensemble Empirical Mode Decomposition (EEMD) with a Time Series Dense Encoder (TiDE) to enhance prediction accuracy. The EEMD algorithm effectively overcomes mode mixing issues in traditional EMD by incorporating white noise perturbations, decomposing raw passenger flow data into physically meaningful Intrinsic Mode Functions (IMFs). At the same time, the TiDE model, a linear encoder–decoder architecture, efficiently handles multi-scale features and covariates without the computational overhead of self-attention mechanisms. Experimental results using Xi’an Metro passenger flow data (2017–2019) demonstrate that EEMD-TiDE significantly outperforms baseline models. This study provides a robust solution for urban rail transit passenger flow forecasting, supporting sustainable urban development. Full article

The automotive industry faces unprecedented pressure to address stringent emissions regulations, evolving consumer expectations, and the urgent need for sustainable mobility solutions. As the global fleet transitions toward lower environmental impact, there is an increasing demand for engineering innovations that can rapidly and cost-effectively modernize existing vehicles. This paper presents a quantitative control-variable analysis, attributing ECU remapping, hardware upgrades (capability envelopes), and water–methanol injection contributions in a production compression-ignited retrofit, achieving 211% power scaling alongside −18% NO_x/−30% opacity compared to baseline values. The study specifically investigates the implementation of ECU tuning, hardware modifications, and auxiliary systems such as WMI, demonstrating their vital role in enhancing vehicle performance, reducing emissions, and extending the operational lifespan of current fleets. By providing actionable engineering solutions, this work supports the industry’s urgent transition to more sustainable and efficient mobility, positioning retrofitting as a cornerstone of future automotive development and environmental compliance. Full article

High-speed train derailments can cause severe vehicle collisions with rail bridges and adjacent infrastructure; however, full-scale evidence for the collision response of trackside intrusion-protection walls and for material measures that limit concrete fragmentation remains scarce. This study addresses this safety-driven knowledge gap by reporting a full-scale collision test of a polyurea-coated reinforced concrete (RC) wall and by clarifying its governing response mechanisms and coating benefits. The inverted T-shaped RC wall was post-anchored to an existing deck and spray-coated with approximately 5 mm polyurea on the collision face and across the wall-footing junction. A 17.68 t container wagon was propelled to 34.59 km/h to reproduce the normal kinetic energy of a representative 68 t KTX car derailing at 300 km/h with a 3° collision angle. High-speed video tracking and post-test mapping captured displacements, rotations, and damage. The wall contained the container wagon without climb-over and without severe local crushing at the collision face; the response was dominated by stable wall-footing rocking, with a peak top displacement of 0.571 m, peak rotation of 19.9°, and residual inclination of approximately 15–17°. The peak collision-force estimate was approximately 1.17 MN, and most input energy (approximately 647–816 kJ) was dissipated through inelastic rocking and sliding while the anchors remained intact. The polyurea layer restrained spalling and fragment release and promoted a more global, repairable rocking-dominated damage state. These results provide rare full-scale benchmarks and mechanistic insight to support performance-based design and retrofit of derailment intrusion-protection walls for improved rail-bridge safety. Full article

This study presents a mixed-integer nonlinear programming (MINLP) framework to optimize the allocation of electric vehicle charging stations (EVCSs) in existing indoor parking facilities. The model minimizes total life-cycle cost by jointly determining charger types and placements while accounting for spatial feasibility and investment constraints. A hybrid search method that combines complete enumeration with dynamic programming is applied to identify the least-cost configuration within geometric and electrical limitations. The results show that configurations combining dual- and quad-port chargers outperform single-port layouts by reducing redundant electrical and installation costs. The analysis confirms that integrating life-cycle costing with spatial feasibility yields a practical decision-support tool for property owners seeking to expand charging capacity within existing facilities. Overall, the framework demonstrates that cost-efficient retrofitting of EV charging infrastructure can be achieved without additional land development, supporting broader sustainability objectives and promoting low-carbon mobility. Future research will extend the model to multiple facility layouts and incorporate sensitivity and uncertainty analyses to evaluate robustness under varying geometric and economic conditions. The findings of this paper provide a practical foundation for future planning studies and demonstrate how cost-optimized retrofit strategies can support the scalable expansion of EV charging infrastructure in existing facilities. Full article

Underground mining environments present elevated occupational health risks, primarily due to substantial exposure to diesel exhaust emissions within confined and poorly ventilated spaces. This study assesses the real-world performance of two advanced retrofit emission control systems—Proventia NOxBuster and Purifilter—installed on underground mining trucks operating in a Spanish mine. Emissions of carbon monoxide (CO), nitric oxide (NO), and nitrogen dioxide (NO₂) were quantified using a Testo 350 multigas analyser, while ultrafine particle (UFP) concentrations were measured with an Engine Exhaust Particle Sizer (EEPS-3090) equipped with a thermodiluter. Controlled tests under both idling and acceleration conditions revealed substantial reductions in pollutant emissions: CO decreased by 60–98%, NO by 51–92%, and NO₂ by 20–87%, depending on the system and operational phase. UFP concentrations during idling dropped by approximately 90%, from 542,000 particles/cm³ in untreated trucks to below 50,000 particles/cm³ in retrofitted vehicles. Under acceleration, the Proventia NOxBuster achieved reductions exceeding 95%. Conversely, Purifilter-equipped trucks exhibited a counterintuitive increase in UFPs within the 5.6–40 nm range, potentially due to ammonia slip events during selective catalytic reduction (SCR). Despite these discrepancies, both systems demonstrated considerable mitigation potential, albeit highly dependent on exhaust temperature (optimal: 200–450 °C), urea dosing precision, and maintenance protocols. This work underscores the necessity of in situ performance verification, regulatory vigilance, and targeted intervention strategies to protect underground workers effectively. Further investigation is warranted into the long-term health benefits, system durability, and nanoparticle emission dynamics under variable load conditions. Full article

This paper explores cost-effective solutions for automated guided vehicle (AGV) through the design and implementation of a low-cost, hoverboard-based line-following AGV tailored for textile manufacturing environments, specifically within sewing plants. The designed AGV leverages the capability of a commercial hoverboard as its mobility platform, significantly reducing development costs while maintaining effective operational performance. Utilizing affordable sensors such as infrared line detectors and ultrasonic sensors, the AGV autonomously navigates pre-defined pathways marked on the factory floor. Its primary function is transporting materials such as fabric bundles and partially or finished products between workstations, addressing common logistical challenges in dynamic and labor-intensive textile production settings. The system is designed for easy integration with both existing plant layouts and information and communication environment, requiring minimal infrastructural changes. Field testing demonstrated the AGV’s reliability, maneuverability, and responsiveness in real-world sewing plant conditions. The proposed solution underscores the potential of retrofitting existing consumer electronics for industrial automation, offering a scalable and economically viable alternative for small- to medium-sized textile enterprises seeking to enhance productivity and workflow efficiency. Full article

Real-time monitoring of lubricants is crucial to the development of transport vehicles. Accidental and fatal failures of components in vehicles occur every day, which threaten the service life of equipment. Inspired by the work of solid–liquid triboelectric nanogenerators (S-L-TENG), we propose a method to retrofit a self-powered sensor for real-time monitoring of lubricating oil leakage. The previous work does not have a systematic study on the influence of various modification methods on the electrification signal of oil-solid contact. This study identifies an optimal modification method with the highest electrification performance by comparing the energizing signals of different modification methods, which provides a new approach for the real-time monitoring of lubricating oil leakage and the detection of lubricating oil impurities. Full article

In recent years, European and national policies on energy efficiency and sustainable construction have promoted a profound rethinking of building practices and strategies for upgrading the existing building stock. With the conversion of Law Decree No. 34 of 19 May 2020 (Decreto Rilancio) into Law No. 77 of 17 July 2020, and of Law Decree No. 76 of 16 July 2020 (Decreto Semplificazioni) into Law No. 120 of 11 September 2020, the tax deduction rate was increased to 110% for expenses related to specific interventions such as seismic risk reduction, energy retrofit, installation of photovoltaic systems, and charging infrastructures for electric vehicles in buildings—commonly known as the Superbonus 110%. Furthermore, the category of “building renovation,” as defined in Presidential Decree No. 380 of 6 June 2001 (art. 3, paragraph 1, letter d), was expanded with specific reference to demolition and reconstruction of existing buildings, allowing—under certain conditions—interventions that do not comply with the original footprint, façades, site layout, volumetric features, or typological characteristics. These measures were designed not only to positively affect household investment levels, thereby significantly contributing to national income growth, but also to support the broader objective of decarbonising the building sector while improving seismic safety. Within this regulatory and policy framework, instruments such as the Superbonus 110% have acted as a driving force for the diffusion of renovation projects aimed at enhancing energy performance and reducing greenhouse gas emissions, in line with the objectives of the European Green Deal and the Energy Performance of Buildings Directive (EPBD). This paper is situated within such a context and examines a real-world case of bio-based renovation admitted to fiscal incentives under the Superbonus 110%. The focus is placed on the procedural framework as well as on the technical, economic, and evaluative aspects, adopting a multidimensional perspective that combines regulatory, operational, and financial considerations. The case study concerns the demolition and reconstruction of a single-family residential chalet, designed according to near-Zero-Energy Building (nZEB) standards, located in the municipality of San Roberto, in the province of Reggio Calabria. The intervention is set within an environmentally and culturally sensitive area, being situated in the Aspromonte National Park and subject to landscape protection restrictions under Article 142 of Legislative Decree No. 42/2004. The aim of the study is to highlight, through the analysis of this case, both the opportunities and the challenges of applying the Superbonus 110% in protected contexts. By doing so, it seeks to contribute to the scientific debate on the interplay between incentive-based regulations, energy sustainability, and landscape–environmental protection requirements, while providing insights for academics, practitioners, and policymakers engaged in the ecological transition of the construction sector. Full article

In low-risk and open environments, such as farms and mining sites, efficient cargo transportation is essential. Despite the suitability of autonomous driving for these environments, its high deployment and maintenance costs limit large-scale adoption. To address this issue, a modular unmanned ground vehicle (UGV) system is proposed, which is adapted from existing platforms and supports both autonomous and manual control modes. The autonomous mode uses environmental perception and trajectory planning algorithms for efficient transport in structured scenarios, while the manual mode allows human oversight and flexible task management. To mitigate the control latency and execution delays caused by platform modifications, an enhanced transformer-based general dynamics model is introduced. Specifically, the model is trained on a custom-built dataset and optimized within a bicycle kinematic framework to improve control accuracy and system stability. In road tests allowing a positional error of up to 0.5 m, the transformer-based trajectory estimation method achieved 94.8% accuracy, significantly outperforming non-transformer baselines (54.6%). Notably, the test vehicle successfully passed all functional validations in autonomous driving trials, demonstrating the system’s reliability and robustness. The above results demonstrate the system’s stability and cost-effectiveness, providing a potential solution for scalable deployment of autonomous transport in low-risk environments. Full article

This study addresses the urgent demand for low-GWP refrigerant alternatives in rail vehicle air-conditioning systems by proposing a novel binary mixture, ZT01 (R13I1/R32 = 0.6/0.4 by mass), as a replacement for R407C. A comprehensive evaluation combining thermodynamic cycle modeling, refrigerant property analysis, and experimental validation shows that ZT01 delivers a coefficient of performance (COP) comparable to R407C, while providing a 45–49% improvement in volumetric cooling capacity, enabling smaller compressor displacement for the same cooling output, and reducing specific compressor work by 13–21%. In addition, ZT01 maintains a lower compression ratio, exhibits non-flammability, is compatible with POE lubricant, and has a GWP of only 308. Life Cycle Climate Performance (LCCP) analysis further indicates a 6.88% reduction in total carbon emissions and a 77.4% reduction in direct emissions compared to R407C, demonstrating that ZT01 is both technically feasible and environmentally sustainable for green retrofitting of rail vehicle HVAC systems. Full article