Browse Topic: Commercial vehicles

Items (6,402)
Decarbonization efforts achieved through electrification in nonroad mobile machinery can realize a reduction in fuel consumption of more than 20%, thanks to concepts familiar to light-duty passenger vehicles. This case study compares the results of a hybrid-electric material handler to its conventional counterpart, utilizing machine-specific drive cycles presented in part one of this paper series. The hybrid prototype features an extended-range electric vehicle (EREV) powertrain that demonstrated substantial energy efficiency improvements. Specifically, there was a reduction in equivalent fuel consumption of 75% when operating in electric-only mode, and 33% when maintaining the battery by charging with an on-board generator. Together, the efficiency improvements can be extrapolated over a low-intensity, 8-h shift characterized by significant idle time and highly dynamic engine load for a 47% reduction in net energy consumption. Key technologies that led to this improvement included
Czarnecki, AlexanderGoodenough, BryantWorm, JeremyRobinette, DarrellLaTendresse, PhilWestman, JohnSubert, DavidHeath, MatthewKiefer, DylanBlack, Andrew
SAE JA6097 (“Using a System Reliability Model to Optimize Maintenance”) shows how to determine which maintenance to perform on a system when that system requires corrective maintenance to achieve the lowest long-term operating cost. While this document may focus on applications to Jet Engines and Aircraft, this methodology could be applied to nearly any type of system. However, it would be most effective for systems that are tightly integrated, where a failure in any part of the system causes the entire system to go off-line, and the process of accessing a failed component can require additional maintenance on other unrelated components.
HM-1 Integrated Vehicle Health Management Committee
Layout optimization is one of the most effective approaches to reduce the power loss induced by turbine wakes. However, the performance of a wind farm is strongly affected by the inflow direction. This paper conducted a sensitivity analysis on a realistic wind farm, Lillgrund Wind Farm, to investigate the sensitivity of inflow direction on the power production of the initial layout and optimal limits. A wake model considering ambient turbulence intensity is adopted together with the wake superposition method to efficiently resolve the flow field in the wind farm. The results indicate that the power production of the initial layout had a significant discrepancy under different inflow directions, and relies on the consistency of inflow direction and layout array directions. The feature of the two main directional sectors is observed from a realistic wind rose. Therefore, two-sector wind roses are adopted in optimization, and the angles of sectors vary among 51 cases. After optimization
Yang, KunDeng, Xiaowei
As the trend toward larger wind turbines continues, the increasing length of blades imposes higher demands on their structural properties. And in actual engineering, wind turbine blade accidents occur frequently. Consequently, ultra-long flexible blades at the hundred-meter scale typically employ composite materials. However, due to the high cost of composites, it is necessary to minimize blade weight to control costs. This study utilizes the MATLAB simulation platform combined with pattern search algorithms to optimize the composite layup of large wind turbine blade structures. The structural properties of the optimized design are then compared and analyzed against those of the reference structure. Simultaneously investigate the impact of different loads on the optimization results. The results demonstrate that the pattern search algorithm can optimize blade layup thickness, spar chordwise position, and spar width, yielding a new blade structure with improved performance. During
Cao, GuangchuanGuo, XiaMeng, Hang
This study investigates the unsteady aerodynamic response, wake evolution, and vortex dynamics of an ultra-large floating offshore wind turbine (FOWT) under coupled motion–wave conditions. A high-fidelity aero–hydrodynamic CFD model is employed for the IEA 22 MW reference turbine. Platform pitch and surge motions are prescribed via sinusoidal functions, and wave conditions are independently introduced by considering two representative sea states (H = 4 m and 7 m) and a no-wave case. Results show that pitch and combined pitch–surge motions significantly amplify unsteady aerodynamic effects, increasing peak power from 81.1 MW (P5S0) to 92.6 MW (P5S5), with periodic negative power output and severe dynamic stall. Under strong motion, waves further raise peak power to 93.4 MW (H7P5S5), indicating a coupled amplification effect. Dynamic stall is mainly triggered by pitch motion, expanding in scope and duration with motion amplitude; wave effects on stall remain limited. Platform motion also
Xie, BinSun, HaiyingChen, Ye
Based on the multi-objective hierarchical optimization solution method, this paper takes both system balance and scheduling economy into account, and constructs a hierarchical collaborative optimization model for the multi-energy complementary system of offshore energy islands. To address the impact of the volatility and randomness of offshore wind farm clusters on the scheduling of energy island systems, the Stochastic Model Predictive Control (SMPC) method is adopted to optimize and solve the scheduling of offshore energy islands. This paper innovatively proposes a scheduling method based on adaptive variable-step stochastic model predictive control. In the rolling optimization process of SMPC, this method tracks the real-time scheduling deviation degree through the deviation reference coefficient and changes the rolling optimization step size. It solves the problems of insufficient scheduling accuracy and being trapped in local optimization in the rolling optimization process of the
Huang, HaochengZhang, JinqiZhou, FengfengYan, QihuiXu, ChangYin, Gaojun
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Tang, GangzhiLiu, JiajunWang, ShuaibinDu, BaochengDeng, Xuefei
The monorail crane is important in mining operations, and its operation affects both safety and efficiency. Currently, fault diagnosis for monorail cranes has several challenges, such as heterogeneous mixing of multimodal data, poor use of knowledge, low real-time requirements, and high deployment costs for large-scale models. To solve these problems, we present an agent framework using a multimodal knowledge graph and a lightweight large model. In particular, we construct a fault knowledge graph for monorail cranes, organizing professional knowledge about components, failure modes, symptoms, and maintenance. By employing retrieval-augmented generation (RAG) technology, the knowledge graph is merged with the Qwen lightweight large model (low-rank adaptation) for fine-tuning to develop a diagnostic agent with task planning, tool invocation and memory. The experimental results show that the agent framework reduces “machine hallucination” and outperforms conventional diagnostic accuracy
Zhang, YixuanXue, ShunBi, XiangWei, XingKang, RanyuJue, JieCheng, Liruiran
This paper presents the design of a novel intelligent monitoring platform for low and medium altitudes, aiming to offer a new solution for the development of intelligent equipment operating in this airspace. Current monitoring tasks are primarily performed by fixed-wing and multi-rotor UAVs, but these platforms face significant technical bottlenecks in flight endurance and monitoring precision. This research aims to address these deficiencies. The platform is based on a small-scale unmanned airship featuring a semi-rigid, hybrid lift-body structure. Improvements were made upon the traditional ellipsoidal hull; the hull profile was optimized using a geometric superposition method, introducing an aerodynamic camber line with a maximum camber (m) of 4% to enhance aerodynamic performance at small angles of attack. In terms of its energy system, the platform is powered by a purely electric energy system composed of solar panels and batteries; solar energy is used during the day, while
Song, ZiangGao, WenxuanCao, XiaochuanZheng, XingZhao, Chong
The design process of mining supports is often complicated due to their intricate structure and numerous dimensional dependencies, leading to a cumbersome modeling process and low design efficiency. To address these challenges, this paper introduces a parametric design system for mining supports built on the SolidWorks platform. The system integrates modular design concepts, module-matching principles, dimension-driven techniques, and API development. By adopting a modular assembly modeling approach, the system offers an efficient solution for managing the dimensional relationships between the various components of mining supports. Additionally, the system supports adaptive processing of 2D engineering drawings, facilitating the rapid design and manufacturing of mining supports. Engineering case studies demonstrate that this system enhances the design efficiency of mining supports by over 90%, significantly shortening the product development cycle, ensuring product quality, and
Rui, LichaoSong, JiahaoYang, ZhiqingLi, HelongDing, Lijian
This article focuses on the problem of high labor cost, low processing efficiency and poor automation of the existing equipment in the postharvest processing of Chinese cabbage. It will design and produce an automated Chinese cabbage processing method called Smart Fresh Pack. Root removal, leaf removal, washing, loading, weighing, packaging and labeling functions were integrated, and smart dexterous intelligence was applied to core concepts and this can be used in the bulk production scenario of supermarkets in the city and countryside Compared with traditional assembly line equipment, obvious advantages in terms of structure, function and processing capacity: Key innovations include: Low-pressure air jet cleaning replaces water washing, which prevents a second contamination and weighing error due to surface moisture; pneumatic gripper and multi-DOF robotic arms combine to package and dynamically weigh simultaneously, streamlining these tasks; machine vision relies on an SSD
Chen, YuhuiZhang, YixuanRuan, JiaZhu, HuayunHe, LianzhengZhao, Ping
This document applies to off-road forestry work machines defined in SAE J1116 or ISO 6814.
MTC4, Forestry and Logging Equipment
This document describes a rigorous engineering test procedure that utilizes industry-accepted data collection and statistical analysis methods to determine the road load and to estimate the aerodynamic drag area of trucks and buses weighing more than 10000 pounds. The test procedure may be conducted on a test track or on a public road under controlled conditions and supported by extensive data collection and data analysis constraints. The estimated aerodynamic-drag-area result represents a single-speed and single-yaw-angle condition. Test results that do not rigorously follow the method described herein shall not be represented as an SAE J2978 result.
Truck and Bus Aerodynamics and Fuel Economy Committee
This SAE Standard is intended to describe the basic types of felling heads, including those with bunching capabilities, that are attachments to a self-propelled machine. Only the major components that are necessary to describe the functions of the felling head, and to apply the principles of the standard are included. Illustrations used are not intended to include all existing felling heads or to describe any particular manufacturer’s variation.
MTC4, Forestry and Logging Equipment
This SAE Standard applies to machines as defined in Appendix A. Some of these machines can travel on-highway but function primarily off-highway.
Cranes and Lifting Devices Committee
TOC
Tobolski, Sue
In order to improve the comfort performance in commercial vehicles, this study proposes a hierarchical control strategy that integrates the evaluation and migration of control algorithms. First, a quarter-vehicle model with four-degree-of-freedom (4-DOF) is constructed, incorporating the dynamics of the wheel, frame, driver’s cab, and seat. The key modal characteristics of the model are then verified through amplitude–frequency analysis, confirming their consistency with the typical vibration patterns observed in actual commercial vehicles, which provides the foundation for subsequent control strategy evaluation and migration. Then, based on a standard two-degree-of-freedom (2-DOF) suspension model, a weighted comprehensive evaluation function is developed to account for comfort, structural safety, handling stability, and both time- and frequency-domain performance indicators. Using this evaluation function, various control algorithms—including Skyhook control (SH), acceleration-based
Pan, TingPang, JianzhongWu, JinglaiZhang, JiuxiangKang, GongZhang, Yunqing
Towing imposes substantial efficiency penalties on both battery-electric vehicles (BEVs) and internal combustion engine (ICE) vehicles, reducing range by 30-50%. This paper presents a proof-of-concept embedded control architecture for distributed trailer propulsion that actively regulates drawbar force to reduce towing loads. Unlike proprietary e-trailer systems requiring specialized hardware, the proposed implementation demonstrates feasibility using commercial off-the-shelf (COTS) components and open-source software. The distributed architecture employs dual Raspberry Pi 4B single-board computers communicating via ROS 2 at 20 Hz. The trailer-mounted controller executes a Simulink-generated control node coordinating load cell acquisition (HX711 ADC), motor CAN bus telemetry, and throttle commands to a 5 kW BLDC traction motor powered by a 5 kWh LiFePO4 battery pack. A vehicle-mounted controller logs OBD-II/CAN validation data. The control pipeline implements cascaded EWMA/Hampel
Joshi, GauravAdelman, IanLiu, JunDonnaway, Ruthie
This paper presents an approach utilizing Nonlinear Model Predictive Control (NMPC) and Unscented Kalman Filter (UKF) to predict system state and control the trajectory of the vehicle with dual trailers in an intersection turn scenario. The UKF estimates vehicle and trailers’ lateral traversal velocity states and the NMPC controls the vehicle acceleration and steering to maintain the vehicle’s desired heading through the turn. The vehicle’s lateral traversal velocity function is formulated using Lyapunov based method which is used as a propagation function in the UKF to improve the estimation accuracy. The lateral traversal velocity is then used as one of the constraints in the NMPC problem. The overall estimation and the control scheme are formulated and assessed in the simulation environment. The simulation results show good tracking and curb avoidance performance.
Malla, Rijan
This paper presents a structured test plan for the development and validation of a Self-Propelled Trailer (SPT), an emerging concept designed to enhance the towing capacity of compact, fuel-efficient vehicles. Unlike conventional trailers, the proposed system integrates electric propulsion and autonomous sensing to actively assist the towing vehicle, reducing engine load and improving both safety and fuel economy. The methodology employs a Design Failure Mode and Effects Analysis (DFMEA) to systematically identify potential risks, while incorporating Society of Automotive Engineers (SAE) standards to guide environmental durability testing (dust, water ingress, gravel impact) and dynamic performance evaluations (gradeability, braking, and stability). A comprehensive set of test procedures is outlined to validate system reliability, robustness, and compliance with established towing requirements. The study demonstrates how powered trailer technology can extend the practical use of
Reilly, CarterPeters, DianeZadeh, Mehrdad
Reliable off-road autonomy requires operational constraints so that behavior stays predictable and safe when soil strength is uncertain. This paper presents a runtime assurance safety monitor that collaborates with any planner and uses a Bekker-based cost model with bounded uncertainty. The monitor builds an upper confidence traversal cost from a lightweight pressure sinkage model identified in field tests and checks each planned motion against two limits: maximum sinkage and rollover margin. If the risk of crossing either limit is too high, the monitor switches to a certified fallback that reduces vehicle speed, increases standoff from soft ground, or stops on firmer soil. This separation lets the planner focus on efficiency while the monitor keeps the vehicle within clear safety limits on board. Wheel geometry, wheel load estimate, and a soil raster serve as inputs, which tie safety directly to vehicle design and let the monitor set clear limits on speed, curvature, and stopping at
Naik, AkshayNorris, WilliamSreenivas, Ramavarapu S.Soylemezoglu, AhmetNottage, Dustin S.Patterson, Albert
This paper builds on last year’s paper presenting DevOps automation in the context of model-based development. Following that paper, we interviewed Simulink users in passenger automotive, motorsports, commercial vehicles, aviation, rocketry, and industrial automation. We discovered that much of the benefit of DevOps platforms to reduce product development cycle time relies on their interactive features. We prototyped new tools to bridge interactive DevOps Git-based platforms with model-based development workflows, and then gathered reactions from another round of interviews. Here we present these interactive DevOps workflows with the feedback from these interviews to contextualize how engineering teams could adopt them to accelerate their own model-based workflows.
Mathews, JonFerrero, SergioTamrawi, AhmedSauceda, Jeremias
In response to increasing customer demand for enhanced passenger comfort and perceived vehicle quality, OEMs in automotive and commercial vehicles are placing significant emphasis on reducing the interior cabin noise. At highway speeds, wind noise is a primary contributor to the overall noise within the vehicle cabin. Conventional approaches to predict vehicle wind noise rely on physical testing, which can only be conducted in the later stages of the design process once a physical prototype is available. Increased adoption of established computational fluid dynamics (CFD) methods has enabled earlier assessment. However, such simulations require several hours to complete, posing a challenge in the context of rapid design iteration cycles. With the growing adoption of artificial intelligence in engineering, machine learning (ML) approaches have been proposed to predict a vehicle’s aerodynamics performance. Nevertheless, development of ML techniques in the context of aeroacoustics
Higgins, JohnFougere, NicolasSondak, DavidSenthooran, SivapalanMoron, PhilippeJantzen, AndreasBi, JingOancea, Victor
Agriculture sector is undergoing a phenomenal transformation, driven by the legislative requirements mandated by countries worldwide to tackle global warming through stringent global emission and on the need to improve operator safety, productivity, particularly on sloped and uneven terrains. Conventional tractors with internal combustion engines (ICEs) have been in use for decades but they often have issues over coordinated control on inclined terrains, especially during load transitions, start-stops, and loader operations. Due to which operators have a critical task of maintaining vehicle stability, controlling rollback on gradients — leading to compromised efficiency, safety risks, and increased fatigue. Global Emission Norms are getting stringent and the justification to end user on the Incremental value proposition is getting difficult to make the products appealing. To address these multifaceted challenges, this paper presents the architecture and functional strategy to increase
M, RojerNatarajan, SaravananMuniappan, Balakrishnan
Crashes involving passenger vehicles increasingly include vehicles equipped with infotainment systems that are unsupported by commercial vehicle system forensics hardware and software. Examiners facing these systems must overcome challenges in acquiring and analyzing user data, requiring an understanding of both digital forensics principles and the proprietary characteristics of the modules. This paper presents a methodology for acquiring data from previously unsupported Lexus infotainment modules, including techniques to bypass CMD42 security locks on SD cards and extract data. Once acquired, the paper outlines methods for analyzing user data through data carving techniques, enabling recovery of information from binary images even when the full file system cannot be reconstructed. Emphasis is placed on maintaining the integrity of the evidence and validating findings through controlled testing. These validation procedures ensure that the recovered information is both accurate and
Burgess, Shanon
When driving in traffic, the wakes of leading vehicles reduce the wind speed experienced by a following vehicle, lowering its drag relative to isolated driving. These wake effects can persist to large inter-vehicle distances, on the order of hundreds of meters, while lateral convection due to cross winds can influence vehicles in adjacent lanes. Wind tunnel testing was conducted at 30% scale for light- and heavy-duty-vehicle models in a large wind tunnel with a traffic-wake simulation system, expanding upon a previous study that examined only heavy vehicles. Three variants of the DrivAer model, four variants of the AeroSUV model, and three variants of a zero-emission heavy-duty-truck model were tested with a range of simulated wake conditions that varied the type, forward distance, and lane position of the wake-source vehicle(s), for a range of yaw angles up to 11°. Results show drag reductions of up to about 10% for the heavy-duty-truck model, and up to about 20% for the passenger
McAuliffe, BrianGhorbanishohrat, FaeghehBarber, Hali
Prior research has validated a reliable method for determining vehicle speed using audio recorded by cameras mounted in vehicles, specifically for rolling passenger vehicle tires. Passenger vehicle tires produce a frequency component directly correlated to vehicle speed when traveling on concrete roadways. However, prior research has not been conducted on audio for rolling commercial vehicle tires, which differ in construction from passenger vehicle tires. The stiffer Commercial tires produce audio signals on roadway surfaces that passenger vehicles tires did not when tested in the prior study. The current research concluded that commercial vehicle tires rolling on various roadway surfaces also generated a frequency that varied with vehicle speed. The purpose of this study was to outline, test, and confirm the source of the speed-dependent frequency and to develop a validated method for use in forensic applications. A modified version of the passenger vehicle tire equation from prior
Vega, Henry V.Cornetto, AnthonyNgo, Long JustinHatab, ZiadHunter, Eric
The demand for improved energy efficiency in real-world vehicle operations continues to grow with technology enhancement. When transporting large cargo loads with passenger pickup trucks and rental trailers, the interaction between vehicle payload, towing configuration, and fuel consumption becomes a key factor in overall system efficiency. Understanding how towing configurations and trailer loading influence fuel consumption and vehicle performance is critical for both consumer guidance and vehicle system design. This study investigates the energy efficiency of U-Haul truck and trailer systems, with a particular focus on the influence of trailer tongue weight. U-Haul truck and trailer simulation models were developed using AVL Vehicle Simulation Model (VSM) software, with an F-350 engine brake-specific fuel consumption (BSFC) map integrated to represent realistic engine performance. Two configurations with equal payload were evaluated: (1) a U-Haul truck alone, and (2) a U-Haul truck
Wang, GangKathadi, MohammadYang, WilliamChen, Yan
A methodology for performing Human Operator Modeling (HOM) using a Caterpillar Model 299D3 XE Compact Track Loader (CTL) is presented. The proposed method uses task analysis techniques to decompose material excavation and moving tasks into smaller, individual tasks presented in a task list. A method for verifying and refining the task list is presented, along with a procedure for identifying relevant human operator sensory information and analyzing human decision making in the context of CTL operation. This methodology is then partially verified through the analysis of a non-expert human operator in Vortex Studio, a realistic construction equipment simulator. A modified test course is executed by a non-expert human operator in the simulation environment, and the recorded data is used to create a quantitative Human Operator Model. From this, a Virtual Operator Model (VOM) feedback controller simulating the performance of the human operator is developed. The VOM is implemented using a
Wang, Orson R.Norris, William R.Patterson, Albert E.Soylemezoglu, AhmetNottage, Dustin S.
This paper presents a hybrid optimization framework that integrates Multi-Physics Topology Optimization (MPTO) with a Neural Network–surrogated Design of Experiments (NN-DOE) to enable lightweight structural design while satisfying crashworthiness, durability, and noise, vibration, and harshness (NVH) requirements under practical casting and packaging constraints. In the proposed MPTO formulation, crash and durability performances are incorporated through equivalent static compliance measures, while NVH performance is assessed using a frequency-domain dynamic stiffness metric, allowing consistent evaluation of trade-offs among competing design requirements. The framework is first demonstrated using a mass-produced passenger-car lower control arm (LCA) as a benchmark component. In this application, MPTO achieves weight reduction under multi-physics objectives by removing non-load-bearing material. Results show that single-discipline optimization produces unbalanced topologies, while
Kim, HyosigSenkowski, AndresGona, KiranSaroha, LalitBoraiah, Mahesh
As Camera Monitoring Systems (CMS) become an integrated part of the driving experience for current automotive and heavy vehicles, keeping the CMS clean from water, dirt, sand, snow and ice is a main focus of the design process in order to avoid safety issues due to obscured visibility. On-road soiling prevention becomes an important feature when designing the camera and sensor systems. Computational Fluid Dynamics (CFD) analysis can be used to facilitate the design process, to provide important information of the cause of the problems and design mitigation mechanism to prevent the visibility issues. Most of existing work focusses on automotive applications. This paper is targeted for heavy vehicle application. Road tests were performed in Alaska by the testing department. Results from the road test were compared to CFD simulation. This comparison showed a good agreement between CFD and road testing, based on the qualitative soiling deposition patterns, rivulet formation and dispersed
He, WeiDasarathan, DevarajLinden, TomPark, Jeongbin
Vehicle pitchover crashes can result in very severe accelerations and forces. Literature and test data available on pitchover crashes is sparse. This paper presents the results of a full-scale pitchover/rollover crash test using an instrumented vehicle in a controlled and documented off-road environment. The test vehicle was driven to the launch point by an off-board operator using remote steering and throttle controls. The test vehicle then experienced an airborne phase during which forward pitching occurred, followed by a front-to-ground impact which induced additional pitchover motion. Then, following the initial front and rear impacts, the vehicle transitioned from a pitchover to rollover motion before coming to rest. The resulting vehicle motion, vehicle damage markings, and ground markings were documented with various slow motion and real time camera views. The test vehicle was instrumented with accelerometers, rotation rate sensors, and other sensors, the results of which
Warner, MarkWarner, WyattSwensen, GrantPerl, Mark
Blending natural gas (NG) with hydrogen (H₂) can improve combustion and engine performance while potentially facilitating the catalytic conversion of methane and other pollutants, resulting in cleaner tailpipe emissions. This study evaluates the impact of H2 on the conversion of methane, CO, and NOx emissions on a commercial three-way catalyst (TWC) in a flow reactor using synthetic gas mixtures that simulate stoichiometric engine exhausts with NG or NG+H₂ combustion. The work examines whether, and how, the additional amount of H₂ in the exhaust stream affects the conversion efficiency of methane and other pollutants. Experiments were conducted with both degreened and aged catalysts under controlled conditions, systematically varying temperature, the air-to-fuel equivalence ratio (λ), and λ modulation. Test conditions covered λ values from 0.996 to 1.000 to represent nominally stoichiometric engine operation with different λ modulation amplitudes, as well as a range of temperatures to
Prikhodko, VitalyWang, MinPark, YeonshilChen, Hai-YingPihl, Josh
Off-road vehicles are typically powered by diesel engines, sized to cover the highest peak loads in their dutycycles. Such applications can be designed with downsized engines, using hybridization to supplement engine power with electrical power for short periods. However, many applications are low-volume and specialized, making it impractical to deploy heavy engineering resources to optimize each one. For this reason, manufacturers tend to produce maid-of-all-work vehicles to cover every situation. This paper demonstrates the benefits of custom hybridization for specialist applications, and addresses the lack of accessible software tools for evaluating such opportunities. Analysis is applied with a fast, low-cost, Concept-based software tool named “ePOP Concept”, suited to original equipment manufacturers (OEMs) who seek to provide custom low-volume vehicles. It allows many different powertrain architectures to be evaluated rapidly at the product planning stage, and can be quickly set
De Salis, RupertFons, Daniel
Off-road autonomous vehicle systems must be able to operate across unstructured and variable terrain while avoiding obstacles. This presents significant challenges in vehicle and control system design, especially for less conventional platforms such as 6×4 vehicles. While forward driving autonomy has developed and matured in recent years, effective reverse navigation remains an under-explored area of vehicle co-design. Reversing 6×4 vehicles have limited rear steering authority, an extended wheelbase, and asymmetric traction, which introduce complex dynamics into any control system that is used. To address this need, a robust and experimentally validated fuzzy logic control architecture for 6×4 reverse navigation was developed during the course of this project. This architecture incorporates both near-field and long-range path data with adaptive outputs controlling steering and velocity based on a rule base that covers the whole vehicle state space. This method has low computational
Dekhterman, Samuel R.Sreenivas, Ramavarapu S.Norris, William R.Patterson, Albert E.Soylemezoglu, AhmetNottage, Dustin
This paper proposes a novel powertrain architecture for the urban Light Commercial Vehicle (LCV) segment, leveraging the compact JLA-2 opposed-piston (OP) engine paired with the reconfigurable JLA-T mild-hybrid architecture. Within SAE literature, OP engines are consistently associated with simplicity. As highlighted by Tom Ryan III (2008 SAE President) in the foreword of Opposed Piston Engines: Evolution, Use, and Future Applications, this architecture is characterized by its manufacturing simplicity” and described as a “relatively simple, robust, and cost effective” power unit solution. The present work builds on this established view. The JLA-2 engine solves traditional packaging constraints by reducing the block width by 30% for horizontal installation and is volumetrically self-sufficient, eliminating external compressors. Although the gear train required for crank synchronization introduces design challenges, explicitly accounted for in our model, the elimination of the cylinder
Nigro, NorbertoAguerre, HoracioCarignano, Mauro GuidoAlonso, José LuisJuni, Carlos A.
Hybrid mining trucks, as core equipment for mine transportation, face high energy consumption and significant fluctuations in power demand during cyclic operations due to prolonged exposure to demanding operating conditions characterized by heavy loads and variable working conditions. To address the issues of high energy consumption and significant fluctuations in power demand during the cyclic operation of mining trucks, this paper proposes a hybrid mining truck energy management strategy based on global SOC (State of Charge) planning and neural network optimization control. First, a powertrain model was developed for a typical operating cycle of a hybrid mining truck, and its accuracy was validated by comparing it with experimental data. Using dynamic programming algorithms to plan the SOC for single-cycle operations provides a rational reference for energy allocation across different operational phases of mining trucks during a single cycle. Next, using the powerful nonlinear
Yang, JianyuZhao, ZhiguoChen, HuiyongLi, TaoZhuang, WenyuShen, PeihongTang, Peng
For off-road driving, particularly on steep grades and over barriers, the engine torque is a key design criterion of off-road vehicles. In conventional powertrains with combustion engines, mechanical all-wheel-drive systems combined with differential locks are used to distribute the torque demand between the front and the rear axle based on wheel-specific traction. With the growing market share of electric powertrains, off-road applications are becoming increasingly relevant for electric passenger cars. In comparison to conventional powertrains, electric all-wheel-drive configurations do not have a mechanical torque transfer between the two axles. If one axle experiences low traction, the second axle can rely on its own torque capability only. Transfer of unused torque of the slipping axle to the other one is not possible. The challenge, therefore, is to specify the right torque requirements for each axle for off-road driving while avoiding over-dimensioning and high powertrain costs
Martin, MichaelWinkelheide, JonasHartmann, LukasSturm, AxelHenze, Roman
Accurate identification of Productive and Non-Productive States or tractor duty cycles—comprising working, idle, and transport states—is critical for performance analysis, fuel optimization, and emissions modeling in agriculture machinery and fleet monitoring. This study explores the application of integrated unsupervised machine learning (ML) techniques to classify duty cycles using GPS-derived parameters such as speed, location variance, and temporal patterns. Unlike supervised approaches, the proposed method does not rely on several labeled engine and vehicle parameters, making it scalable and adaptable across diverse operational contexts. Clustering algorithm DBSCAN (Density-Based Spatial Clustering of Applications with Noise) in integration with hybrid rule-based and a road feature is employed to segment GPS data into distinct behavioral states. Feature engineering focuses on extracting motion signatures and spatial-temporal features that correlate with operational modes
Maharana, Devi prasadGangsar, PurushottamDharmadhikari, NitinPandey, Anand Kumar
High-precision estimation of key vehicle–road state parameters is crucial for ensuring the accurate and safe control of mining trucks (MT), as well as for reliable trajectory tracking. Among these parameters, the vehicle sideslip angle is particularly critical for assessing and predicting lateral stability. However, its direct measurement is challenging, and its estimation typically depends on an accurate characterization of tire cornering stiffness. For MT, large variations in loading conditions (from empty to fully loaded) pose significant challenges to sideslip angle estimation due to the resulting nonlinearity and variability of tire cornering stiffness. To address this issue, a novel joint estimation framework integrating the Moving Horizon Estimation (MHE) and Square-Root Cubature Kalman Filter (SCKF) is proposed to simultaneously achieve high-precision estimation of both tire cornering stiffness for each tire and vehicle sideslip angle. In this framework, the cornering stiffness
Xia, XueShen, PeihongJiao, LeqiLi, TaoChen, HuiyongZhao, KunJiao, LeqiZhao, Zhiguo
Direct Current (DC) fast charging enables supply of megawatt (MW) scale DC power to the large battery systems of Heavy-Duty Electric Vehicles (HDEVs), such as electric trucks, buses, ferry and construction machinery. This contrasts with Alternating Current (AC) charging, which is limited by the capacity of the On-Board Charger (OBC) that converts AC to DC to charge the battery. In DC fast charging, however, the Electric Vehicle Supply Equipment (EVSE) delivers DC power directly to the HDEVs, bypassing the OBC. The feasibility of fast DC charging has been driven by advancements in semiconductor technology offering higher voltage and current handling capabilities as well as improvements in battery energy density. Ongoing research indicates continued growth in both semiconductor power handling and battery storage capacity, further strengthening the case for fast DC charging. Key benefits include significantly higher charging efficiency, drastically reduced charging times, and lower driver
Rahman, Md Rakib-UrDobrzynski, Daniel
This article investigates the optimization problem of fuel economy for heavy-duty commercial vehicles. A Dynamic Programming–Based Fuel-Saving Predictive Cruise Control (DP-FSPCC) method is proposed, which is based on the Bellman optimality principle and uses the cost function to evaluate the optimal feedback control gain, thereby improving the fuel economy of heavy-duty commercial vehicles on complex roads with varying slopes. To address the issues of low accuracy in road feature representation and poor adaptability to different driving conditions in existing slope reconstruction algorithms, the road ahead is dynamically segmented for high-precision processing by integrating ADASIS (Advanced Driver Assistance Systems Interface Specifications) map information with significant turning point detection and dynamic sensitivity analysis. An engine fuel consumption mapping model based on local gradient information is established to provide an accurate cost function for dynamic programming
Jin, DapengShuai, YueWu, XinJia, TongQiao, ZhiyuanChang, ShiweiMu, Tong
Why precision engineering is defining confidence in next-generation internal combustion engines. In 2026, the global transport industry, and particularly the automotive industry, finds itself under competing pressures. Regulators are tightening emissions standards, with new regulations such as the EU's Euro 7 being proposed to reduce air pollution in line with net-zero ambitions. Fleet operators are managing ever-aging vehicle populations in uncertain economic conditions, and policymakers are accelerating mandates for sustainable fuels, with countries like the UK moving forward with a Zero Emission Vehicle mandate by 2035. Across passenger vehicles, commercial transport, and off-highway machinery, engineers are now tasked with delivering measurable carbon reduction using a combination of electrification, advanced internal combustion engines (ICE) and fuel innovation without compromising safety, durability or performance.
Anderson, Todd
Driven by the dual-carbon goals of “peak carbon emissions” and “carbon neutrality,” improving energy efficiency in electric construction machinery has become a key focus. This study proposes an energy-saving torque control strategy for the traction motor of electric wheel loaders, aiming to reduce drive system energy consumption. The innovation lies in coupling parameter optimization of the pedal–torque mapping and regenerative braking to enhance overall efficiency. An electric model was built using Cruise and validated against real-world V-cycle test data, showing good agreement with an average relative error of 4.08%. Based on the model, two optimized control strategies were developed and evaluated through simulations and field tests. The results showed energy savings of 7.08% and 16.18% in simulation, and 6.83% and 15.51% in tests, respectively, demonstrating the effectiveness and practical value of the proposed method.
Ming, QiaohongWang, YangyangWang, Feng
This article aims to determine the time to rollover (TTR) of a tractor semi-trailer vehicle (TSTV). It uses a full dynamics model for assessment, specifically applying multi-body system analysis and Newton–Euler Equations with a nonlinear tire model. The model is applied to investigate velocities ranging from 40 km/h to 80 km/h and magnitude of steering angles ranging from 12.5° to 300°. The times at which the Load Transfer Ratio (LTR), Roll Safety Factor (RSF), and lateral acceleration reach their maximum values are evaluated. The survey results demonstrate the impact of velocity and steering wheel angle on the time it takes for the LTR, RSF, and lateral acceleration to reach their maximum values. The time interval between the RSF reaching 1 and the LTR reaching 1 range from 0.144 s to 0.655 s. Similarly, the time it takes for the tractor body’s lateral acceleration to peak and the LTR to reach 1 varies between 0.228 s and 1.555 s. Additionally, the time interval from when the semi
Hung, Ta TuanKhanh, Duong Ngoc
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