Search Results (12)

The reclamation of exhausted open-pit coal mines is an energy-intensive and costly process. Traditional methods offer no economic return. This study explores the feasibility of using autonomous electric dump trucks (EDTs) to fill the pit, leveraging regenerative braking during descent to generate energy and reduce operational costs. A comprehensive energy balance model was developed based on the operational cycle of the Komatsu HD605-7 (E-Dumper) in the unique downhill-loaded logistics of the Pery quarry. The model incorporates vehicle dynamics equations, including rolling resistance, gradient, and aerodynamic forces, to calculate net energy consumption per cycle. Three energy storage system (ESS) configurations were compared: NMC/NCA batteries, LiFePO₄ (LFP) batteries, and a hybrid LFP + supercapacitor (SC) system. Simulation results demonstrate that the net energy per cycle decreases with increasing payload capacity, even becoming negative (net energy generation) for loads above 110 tons due to powerful regenerative braking on the 13% descent grade. The hybrid LFP + SC system proved most efficient, achieving the lowest specific energy consumption (kWh/ton) by effectively capturing high-power regenerative currents. While LFP batteries have a lower energy density, their superior cycle life, thermal stability, and safety make them the optimal choice for the harsh mining environment. The proposed operation strategy, utilizing EDTs in a downhill-loaded cycle, transforms mine reclamation from a cost center into a potentially energy-neutral or even energy-positive process. A hybrid ESS with LFP batteries and supercapacitors is recommended as the most reliable and efficient solution for this specific application. Full article

Electric rope shovels play a critical role in open-pit mining, where their automation and operational efficiency directly affect productivity. This paper presents a LiDAR-based relative positioning method to determine the spatial relationship between the ERS and mining trucks. The method utilizes dynamic DBSCAN for noise removal and RANSAC for truck edge detection, enabling robust and accurate localization. Leveraging this positioning data, a time-optimal trajectory planning strategy is proposed specifically for autonomous swing motion during the unloading process. The planner incorporates velocity and acceleration constraints to ensure smooth and efficient movement, while obstacle avoidance mechanisms are introduced to enhance safety in constrained excavation environments. To execute the planned trajectory with high precision, a neural network-based sliding-mode controller is designed. An adaptive RBF network is integrated to improve adaptability to model uncertainties and external disturbances. Experimental results on a scaled-down prototype validate the effectiveness of the proposed positioning, planning, and control strategies in enabling accurate and autonomous swing operation for efficient unloading. Full article

Open-pit mining involves the use of vehicles with high load capacity and satisfactory mobility. As experience shows, these requirements are fully met by pneumatic wheeled dump trucks, the traction drives of which can be made using thermal or electric machines. The latter are preferable due to their environmental friendliness. Unlike dump trucks with thermal engines, which require fuel to be injected into them, electric trucks can be powered by various options of a power supply: centralized, autonomous, and combined. This paper highlights the advantages and disadvantages of different power supply systems depending on their schematic solutions and the quarry parameters for all the variants of the power supply of the dumper. Each quantitative indicator of each factor was changed under conditions consistent with the others. The steepness of the road elevation in the quarry and its length were the factors under study. The studies conducted show that the energy consumption for dump truck movement for all variants of a power supply practically does not change. Another group of factors consisted of electric energy sources, which were accumulator batteries and double electric layer capacitors. The analysis of energy efficiency and the regenerative braking system reveals low efficiency of regeneration when lifting the load from the quarry. In the process of lifting from the lower horizons of the quarry to the dump and back, kinetic energy is converted into heat, reducing the efficiency of regeneration considering the technological cycle of works. Taking these circumstances into account, removing the regenerative braking systems of open-pit electric dump trucks hauling soil or solid minerals from an open pit upwards seems to be economically feasible. Eliminating the regenerative braking system will simplify the design, reduce the cost of a dump truck, and free up usable volume effectively utilized to increase the capacity of the battery packs, allowing for longer run times without recharging and improving overall system efficiency. The problem of considering the length of the path for energy consumption per given gradient of the motion profile was solved. Full article

The purpose of this review is to comprehensively compare the developments and challenges in the energy performance of unconventional pneumatic suspension (PS) and hydropneumatic suspension (HPS), which have special applications in passenger cars, trucks, military vehicles and agricultural equipment. The main differences between PS and HPS, as well as their advantages and disadvantages, are presented. The PS system is discussed along with its principle of operation, advances in development, principle of operation of air springs, their models, characteristics, vibration isolation, and simulation models. The HPS system is discussed, along with its operational principles, progress in development, models, and characteristics. This review also discusses new trends in HPS development, such as the effect of a pressure fluctuation damper (PFD) placed in a hydraulic cylinder on the damping performance index (DPI) of an HPS under off-road driving conditions. It highlights innovative solutions that can be expected in the future in PS and HPS systems, with the expectations of drivers and passengers. The review focused on trends and challenges in PS and HPS development, such as integration with electronics, smart solutions, customized solutions, emphasis on compliance with ecological and environmental requirements, and applications in electric vehicles (EVs) and autonomous vehicles (AVs). Full article

In recent years, parcel volumes have reached record highs, prompting the logistics industry to explore innovative solutions to meet growing demand. In densely populated areas, delivery robots offer a promising alternative to traditional truck-based delivery systems. These autonomous electric robots operate on sidewalks and deliver time-sensitive goods, such as express parcels, medicine and meals. However, their limited cargo capacity and battery life require a return to a depot after each delivery. This challenge can be modeled as an electric vehicle-routing problem with soft time windows and single-unit capacity constraints. The objective is to serve all customers while minimizing the quadratic sum of delivery delays and ensuring each vehicle operates within its battery limitations. To address this problem, we propose a mixed-integer quadratic programming model and introduce an enhanced formulation using a layered graph structure. For this layered graph, we present two solution approaches based on relaxations that reduce the number of nodes and arcs compared to the expanded formulation. The first approach, Iterative Refinement, solves the current relaxation to optimality and refines the graph when the solution is infeasible for the expanded formulation. This process continues until a proven optimal solution is obtained. The second approach, Branch and Refine, integrates graph refinement into a branch-and-bound framework, eliminating the need for restarts. Computational experiments on modified Solomon instances demonstrate the effectiveness of our solution approaches, with Branch and Refine consistently outperforming Iterative Refinement across all tested parameter configurations. Full article

The aviation industry has proposed multiple solutions to reduce fuel consumption, air pollution, and noise at airports, one of which involves deploying electric trucks for aircraft towing between the stand and the runway. However, the introduction of tow trucks results in increased surface traffic, posing challenges from the perspective of air traffic controllers (ATCOs). Various solutions involving automated planning and execution have been proposed, but many are constrained by their inability to manage multiple active runways simultaneously, and their failure to account for the tow truck battery state of charge during assignments. This paper presents a novel system for taxi operations that employs autonomous tow trucks to enhance ground operations and address deficiencies in existing approaches. The system focuses on identifying conflict-free solutions that minimise taxi-related delays and route length while maximising the efficient use of the tow trucks. The algorithm operates at a strategic level and uses a centralised approach. It has the capacity to cater for multiple active runways and considers factors such as the tow truck battery state of charge and availability of charging stations. Furthermore, the proposed algorithm is capable of scheduling and routing tow trucks for aircraft taxiing without generating traffic conflicts. Full article

The rapid development of modern logistics and e-commerce highlights the importance of exploring various modes of transportation in the last-mile delivery (LMD) process. However, no comprehensive studies exist in the literature exploring all modes of LMD transportation, the changes in these transportation modes, and the commonalities between them. In this study, we address this gap by conducting a systematic review of 150 academic journal articles utilizing a combination of the Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) content analysis and text mining analysis. Nine primary transportation methods (parcel lockers, autonomous drones, trucks, bicycles, crowd logistics, electric vehicles, tricycles, autonomous robots, and autonomous vehicles) are identified in this research. Additionally, we provide an analysis of the historical changes in these transportation modes in LMD. Using a bottom-up induction method, we identify the three major clusters of scholarly focus in the LMD literature: emphasis on value co-creation between consumers and logistics providers, practical delivery performance (path optimization or algorithms), and environmental friendliness. Further, we analyze the main themes under each cluster, leading to the identification of opportunities, challenges, and future research agendas. Our findings have implications for scholars, policymakers, and other stakeholders involved in LMD transportation modes. Full article

This study presents an analysis of the charging infrastructure requirements for autonomous electric trucks (AETs) in a specified geographical region, focusing on the state of Texas as a case study. A discrete-time, agent-based model is used to simulate the AET fleet and consider various model parameters such as trip distance/duration, the number of trips, and charging speeds. The framework incorporates unique properties of the Texas road network to assess the sensitivity of charging infrastructure needs. By synergizing electrification and automation, AETs offer benefits such as reduced carbon emissions, enhanced transportation safety, decreased congestion, and improved operational costs for fleets. By simulating daily trips and energy consumption patterns, an analysis of the charging infrastructure needs for cities along the Texas highway triangle formed by I-35, I-45 and I-10 revealed that the total charging energy and average charging power for these major cities ranges between 443~533 MWh/day and 18.5~22 MW, with costs in the range of USD $7.74~$15.93 million for each city, depending on charging infrastructure design and exclusive of any enhancements to the distribution grid infrastructure needed to support the charging infrastructure. This data-driven approach may be replicated for other regions by adapting the simulation parameters to allow policymakers and stakeholders to assess the charging infrastructure requirements and related investments needed to support the transition to electric and autonomous heavy-duty trucking. Full article

The regional parliament of Tyrol in Austria adopted the climate, energy, and resources strategy “Tyrol 2050 energy autonomous” in 2014 with the aim to become climate neutral and energy autonomous. “Use of own resources before others do, or have to do” is the main principle within this long-term strategic approach, in which the “power on demand” process is a main building block and the “power-to-hydrogen” process covers the intrinsic lack of a long-term, large-scale storage of electricity. Within this long-term strategy, the national research and development (R&D) flagship project WIVA P&G HyWest (ongoing since 2018) aims at the establishment of the first sustainable, business-case-driven, regional, green hydrogen economy in central Europe. This project is mainly based on the logistic principle and is a result of synergies between three ongoing complementary implementation projects. Among these three projects, to date, the industrial research within “MPREIS Hydrogen” resulted in the first green hydrogen economy. One hydrogen truck is operational as of January 2023 in the region of Tyrol for food distribution and related monitoring studies have been initiated. To fulfil the logistic principle as the main outcome, another two complementary projects are currently being further implemented. Full article

Truck-Shovel (TS) systems are the most common mining system currently used in large surface mines. They offer high productivity combined with the flexibility to be rapidly relocated and to adjust load/haul capacity and capital expenditure according to market conditions. As the world moves to decarbonise as part of the transition to net zero emission targets, it is relevant to examine options for decarbonising the haulage systems in large surface mines. In-Pit Crushing and Conveying (IPCC) systems offer a smaller environmental footprint regarding emissions, but they are associated with a number of limitations related to high initial capital expenditure, capacity limits, mine planning and inflexibility during mine operation. Among the emerging technological options, innovative Trolley Assist (TA) technology promises to reduce energy consumption for lower carbon footprint mining systems. TA systems have demonstrated outstanding potential for emission reduction from their application cases. Battery and energy recovery technology advancements are shaping the evolution of TAs from diesel-electric truck-based patterns toward purely electrified BT ones. Battery Trolley (BT) systems combined with autonomous battery-electric trucks and Energy Recovery Systems (ERSs) are novel and capable of achieving further significant emission cuts for surface mining operations associated with safety, energy saving and operational improvements. This article reviews and compares electrification alternatives for large surface mines, including IPCC, TA and BT systems. These emerging technologies provide opportunities for mining companies and associated industries to adopt zero-emission solutions and help transition to an intelligent electric mining future. Full article

The boom in the electronics industry has made a variety of credit card-sized computer systems and plenty of accompanying sensing and acting elements widely available, at continuously diminishing cost and size levels. The benefits of this situation for agriculture are not left unexploited and thus, more accurate, efficient and environmentally-friendly systems are making the scene. In this context, there is an increasing interest in affordable, small-scale agricultural robots. A key factor for success is the balanced selection of innovative hardware and software components, among the plethora being available. This work describes exactly the steps for designing, implementing and testing a small autonomous electric vehicle, able to follow the farmer during the harvesting activities and to carry the fruits/vegetables from the plant area to the truck location. Quite inexpensive GPS and IMU units, assisted by hardware-accelerated machine vision, speech recognition and networking techniques can assure the fluent operation of a prototype vehicle exhibiting elementary automatic control functionality. The whole approach also highlights the challenges for achieving a truly working solution and provides directions for future exploitation and improvements. Full article

This paper proposes a predictive driver coaching (PDC) system for fuel economy driving for hybrid electric trucks using upcoming static map and dynamic traffic data. Unlike traditional methods that optimize over engine torque and brake to obtain a speed profile, we propose to optimize over driving modes of trucks to achieve a trade-off between fuel consumption and trip time. The optimal driving mode is provided to the driver as a coaching recommendation. To obtain the optimal solution, the truck dynamics are firstly modeled as a hybrid controlled switching dynamical system with autonomous subsystems and then a hybrid optimal control problem (HOCP) is formulated. The problem is solved using an algorithm based on discrete hybrid minimum principle. A warm-start strategy to reduce algorithmic iterations is used by employing a shrinking horizon strategy. In addition, an extensive analysis of the proposed algorithm is provided. We prove that the the coasting mode is never optimal given the truck configuration and and we provide a guideline for tuning parameters to maintain the optimal mode sequence. Finally, the algorithm is validated using real-world data from baseline driving tests using a DAF hybrid truck. Significant reduction in fuel consumption is achieved when the data is perfectly available. Full article