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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 The use of appropriate loads and regulations is of great importance in weld fatigue assessment of rail on-track maintenance equipment and similar vehicles for optimized design. The regulations and available loads, however, are often generalized for several categories, which proves to be overly conservative for some specific categories of machines. EN (European Norm) and AAR (Association of American Railroads) regulations play a pivotal role in determining the applicable loads and acceptance criteria within this study. The availability of track-induced fatigue load data for the cumulative damage approach in track maintenance machines is often limited. Consequently, the FEA-based validation of rail track maintenance equipment often resorts to the infinite life approach rather than cumulative damage approach for track-induced travel loads, resulting in overly conservative designs.

Abstract The two-branch exhaust of an asymmetric twin-scroll turbocharged engine are asymmetrically and periodically complicated, which has great impact on turbine matching. In this article, a matching effect of turbine speed parameter on asymmetric twin-scroll turbines based on the exhaust pulse energy weight distribution of a heavy-duty diesel engine was introduced. First, it was built as an asymmetric twin-scroll turbine matching based on exhaust pulse energy distribution. Then, by comparing the average matching point and energy matching points on the corresponding turbine performance map, it is revealed that the turbine speed parameter of energy matching points was a significant deviation from the turbine speed parameter under peak efficiency, which leads to the actual turbine operating efficiency lower than the optimal state.

Abstract Heavy-duty on-road engines are expected to conform to an ultralow NOx (ULNOx) standard of 0.027 g/kWh over the composite US heavy-duty transient federal test procedure (HD-FTP) cycle by 2031, a 90% reduction compared to 2010 emissions standards. Additionally, these engines are expected to conform to Phase 2 greenhouse gas regulations, which require tailpipe CO2 emissions under 579 g/kWh. This study experimentally demonstrates the ability of high fuel stratification gasoline compression ignition (HFS-GCI) to satisfy these emissions standards. Steady-state and transient tests are conducted on a prototype multi-cylinder heavy-duty GCI engine based on a 2010-compliant Cummins ISX15 diesel engine with a urea-SCR aftertreatment system (ATS). Steady-state calibration exercises are undertaken to develop highly fuel-efficient GCI calibration maps at both cold-start and warmed up conditions.

Abstract This article presents the methodical development of a subframe for a novel on-the-road-modular vehicle concept, which was developed for the U-Shift project. The subframe serves as the basis for a modular chassis. This chassis offers the possibility to exchange chassis components by the operator, which means after completion by the manufacturer, and thus to adapt the vehicle to different purposes. According to the applied methodology, the relevant wheel loads are determined and a geometric reference model is created. By defining the relevant load cases, the forces acting on the subframe, and thus the physical boundary conditions, can be determined from the wheel loads. In addition to the wheel loads and the geometric boundary conditions, no other vehicle parameters are required for the development of the subframe. The results of the topology optimization are used to identify areas of the geometric reference model that are not exposed to high loads.

Abstract This study underscores the benefits of refining the intralogistics process for small- to medium-sized manufacturing businesses (SMEs) in the engineer-to-order (ETO) sector, which relies heavily on manual tasks. Based on industrial visits and primary data from six SMEs, a new intralogistics concept and process was formulated. This approach enhances the value-added time of manufacturing workers while also facilitating complete digital integration as well as improving transparency and traceability. A practical application of this method in a company lead to cutting its lead time by roughly 11.3%. Additionally, improved oversight pinpointed excess inventory, resulting in advantages such as reduced capital needs and storage requirements. Anticipated future enhancements include better efficiency from more experienced warehouse staff and streamlined picking methods. Further, digital advancements hold promise for cost reductions in administrative and supportive roles.

Abstract Being an engineer-to-order (ETO) operating industry, the control cabinet industry faces difficulties in process and workplace optimizations due to changing requirements and lot size one combined with volatile orders. To optimize workplaces for employees, current literature is focusing on ergonomic designs, providing frameworks to analyze workplaces, leaving out the optimal design for productivity. This work thus utilizes a Kano analysis, collecting empirical data to identify essential design requirements for assembly workplaces, incorporating input from switchgear manufacturing employees. The results emphasize the need for a balance between ergonomics and efficiency in workplace design. Surprisingly, few participants agree on the correlation between improved processes and workspaces having a positive impact on their well-being and product quality.

Abstract The adoption of battery electric trucks (BETs) as a replacement for diesel trucks has potential to significantly reduce greenhouse gas emissions from the freight transportation sector. However, BETs have shorter driving range and lower payload capacity, which need to be taken into account when dispatching them. This article addresses the energy-efficient dispatching of BET fleets, considering backhauls and time windows. To optimize vehicle utilization, customers are categorized into two groups: linehaul customers requiring deliveries, where the deliveries need to be made following the last-in-first-out principle, and backhaul customers requiring pickups. The objective is to determine a set of energy-efficient routes that integrate both linehaul and backhaul customers while considering factors such as limited driving range, payload capacity of BETs, and the possibility of en route recharging.

Abstract The drone logistics distribution method, with its small size, quick delivery, and zero-touch, has progressively entered the mainstream of development due to the global epidemic and the rapidly developing global emerging logistics business. In our investigation, a drone and a delivery man worked together to complete the delivery order to a customer’s home as quickly as possible. We realize the combined delivery network between drones and delivery men and focus on the connection and scheduling between drones and delivery men using existing facilities such as ground airports, unmanned stations, delivery men, and drones. Based on the dynamic-vehicle routing problem model, the establishment of a delivery man and drone with a hybrid model, in order to solve the tarmac unmanned aerial vehicle for take-out delivery scheduling difficulties, linking to the delivery man and an adaptive large neighborhood search algorithm solves the model.

Abstract The sinking and trimming of the hull in the channel would directly affect the handling and navigation safety of the ship. In view of the ship sinking, a series of empirical formulas to estimate the subsidence have been put forward for vessel in spacious shallow water areas. However, most of the equations are based on seagoing vessels. They are not suitable for inland ships with small scales, shallow drafts, and narrow navigation width. Till now, research on ship squat in intermediate channel has not yielded more practical results. Here, a generalized physical model is used to study the sinking of 500t class ships in restricted intermediate channel under different channel widths, water depths, and speeds. The main factors affecting the squat are analyzed, the empirical relation is compared with the measured squat. The Barrass equation is modified, and the calculation relation of the settlement suitable for inland river ships is proposed.

Abstract Reviewers

Abstract Parking an articulated vehicle is a challenging task that requires skill, experience, and visibility from the driver. An automatic parking system for articulated vehicles can make this task easier and more efficient. This article proposes a novel method that finds an optimal path and controls the vehicle with an innovative method while considering its kinematics and environmental constraints and attempts to mathematically explain the behavior of a driver who can perform a complex scenario, called the articulated vehicle park maneuver, without falling into the jackknifing phenomena. In other words, the proposed method models how drivers park articulated vehicles in difficult situations, using different sub-scenarios and mathematical models.

Abstract Vehicle vibration is the key consideration in the early stage of vehicle development. The most dynamic system in a vehicle is the powertrain system, which is a source of various frequency vibration inputs to the vehicle. Mostly for powertrain mounting system design, only the uncoupled powertrain system is considered. However, in real situations, other subsystems are also attached to the powertrain unit. Thereby, assuming only the powertrain unit ignores the dynamic interactions among the powertrain and other systems. To address this shortcoming, a coupled powertrain and driveline mounting system problem is formulated and examined. This 16 DOF problem is constructed around a case of a front engine-based powertrain unit attached to the driveline system, which as an assembly resting on other systems such as chassis, suspensions, axles, and tires.

Abstract Numerous researchers are committed to finding solutions to the path planning problem of intelligence-based vehicles. How to select the appropriate algorithm for path planning has always been the topic of scholars. To analyze the advantages of existing path planning algorithms, the intelligence-based vehicle path planning algorithms are classified into conventional path planning methods, intelligent path planning methods, and reinforcement learning (RL) path planning methods. The currently popular RL path planning techniques are classified into two categories: model based and model free, which are more suitable for complex unknown environments. Model-based learning contains a policy iterative method and value iterative method. Model-free learning contains a time-difference algorithm, Q-learning algorithm, state-action-reward-state-action (SARSA) algorithm, and Monte Carlo (MC) algorithm.

Abstract The development of predictive maintenance has become one of the most important drivers of innovation, not only in the maritime industry. The proliferation of on-board and remote sensing and diagnostic systems is creating many new opportunities to reduce maintenance costs and increase operational stability. By predicting impending system faults and failures, proactive maintenance can be initiated to prevent loss of seaworthiness or operability. The motivation of this study is to optimize predictive maintenance in the maritime industry by determining the minimum useful remaining lead-acid battery capacity measurement frequency required to achieve cost-efficiency and desired prognostic performance in a remaining battery capacity indication system. The research seeks to balance operational stability and cost-effectiveness, providing valuable insight into the practical considerations and potential benefits of predictive maintenance.

Abstract The ability to predict the durability of a structure depends on the knowledge of operating loads experienced by the structure. Typically, multi-body dynamics (MBD) models are used to cascade measured wheel loads to hard points. However, in this approach, there are many sources by which errors creep into cascaded forces. Any attempt to reduce sources of such errors is time consuming and costly. In typical program development timelines, it is very difficult to accommodate such model calibration efforts. Commercial load cells exist in the industry to give engineers insight into understanding the complex real-world loading of their structures. A significant limitation to the use of load cells is that the structure needs to be modified to accept the load cell, and not all desired loading degrees of freedom (DOFs) can be measured. One of the innovative solutions to calculate operating loads is to convert the structure itself into its own load transducer.

Abstract Articulated vehicles form an important part of our society for the transport of goods. Compared to rigid trucks, tractor-trailer combinations can transport huge quantities of load without increasing the axle load. The fifth wheel (FW) acts as a bridge between the tractor and trailer, which can be moved within the range to achieve rated front and rear axle loads. When the FW is moved front, it adversely affects the cab dynamics and cab suspension forces. Compared to the cab pitch and roll, yaw motion increases drastically. The current study tries to address this issue by providing reaction rod links in the rear cab suspension. In this study, a 4×2 tractor with a three-axle semitrailer is considered by keeping the FW at its frontmost position, which is the worst-case scenario for a cab. Three different cases of reaction rod arrangement and its influence on cab dynamics are studied in comparison with a model without reaction rods.

Abstract Certain advanced driver assistance systems (ADAS) have the potential to boost energy efficiency in real-world scenarios. This article details a radar-based driver assistance scheme designed to minimize fuel consumption for a commercial vehicle by predictively optimizing braking and driving torque inputs while accommodating the driver’s demand. The workings of the proposed scheme are then assessed with a novel integration of the driver assistance functionality in randomized traffic microsimulation. Although standardized test procedures are intended to mimic urban and highway speed profiles for the purposes of evaluating fuel economy and emissions, they do not explicitly consider the interactions present in real-world driving between the ego vehicle equipped with ADAS and other vehicles in traffic. This article presents one approach to address the drawback of standardized test procedures for evaluating the fuel economy benefits of ADAS technologies.

Abstract With the rapid development of the Internet and intelligent control technology, intelligent transportation has become a research hotspot in building a smart city. Under the background of intelligent transportation, it is particularly important to effectively evaluate the rail transit as the framework of urban public transport in this study, and fuzzy mechanism is introduced to optimize the support vector machine (SVM), and on this basis, analytic hierarchy process (AHP) and SVM are combined to improve the classification accuracy and improve the rail transit operation safety evaluation index system. The experimental results show that the classification accuracy of the fuzzy SVM combined with AHP is above 85% on all the datasets, and it can effectively eliminate the less-relevant indicators. In the actual evaluation of Shanghai Rail Transit safety, the prediction accuracy exceeded 80% and the highest reached 94.51%.

Abstract A modelling tool has been developed for the prediction of fuel effects on the performance and exhaust emissions of a heavy-duty diesel engine. Recurrent neural network models with duty-cycle, engine control, and fuel property parameters as inputs were trained with transient test data from a 15-liter heavy-duty diesel engine equipped with a common-rail fuel injection system and a variable geometry turbocharger. The test fuels were formulated by blending market diesel fuels, refinery components, and biodiesel to provide variations in preselected fuel properties, namely, hydrogen-to-carbon (H/C) ratio, oxygen-to-carbon (O/C) ratio, derived cetane number (CN), viscosity, and mid- and end-point distillation parameters. Care was taken to ensure that the correlation between these fuel properties in the test fuel matrix was minimized to avoid confounding model input variables.