scholarly journals Bucket Trajectory Optimization under the Automatic Scooping of LHD

Energies ◽  
2019 ◽  
Vol 12 (20) ◽  
pp. 3919
Author(s):  
Yu Meng ◽  
Huazhen Fang ◽  
Guodong Liang ◽  
Qing Gu ◽  
Li Liu
Keyword(s):  
Energy Consumption ◽  
Trajectory Optimization ◽  
Reaction Force ◽  
Minimum Energy ◽  
Earth Pressure ◽  
Force Model ◽  
Minimum Energy Consumption ◽  
One Step ◽  
The One ◽  
Step Step

We propose an optimal planning scheme of the bucket trajectory in the LHD (Load-Haul-Dump) automatic shoveling system to improve the effectiveness of the scooping operation. The research involves simulation of four typical shoveling methods, optimization of the scooping trajectory, establishment of a reaction force model in the scooping process and determination of optimal trajectory. Firstly, we compared the one-step, step-by-step, excavation and coordinated shoveling method by the Engineering Discrete Element Method (EDEM) simulation. The coordinated shoveling method becomes the best choice on account of its best comprehensive performance among the four methods. Based on the coordinated shoveling method, the shape of the optimized trajectory can be roughly determined. Then, we established a model of bucket force during the shoveling process by applying Coulomb’s passive earth pressure theory for the purpose of calculating energy consumption. The trajectory is finally determined through optimizing the minimum energy consumption in theory. The theoretical value is verified by the EDEM simulation.

THE USE OF ELECTROLYSIS OF AQUEOUS SOLUTIONS AND MOLTEN SALTS FOR THE SYNTHESIS OF OXIDE BRONZES

2021 ◽  
pp. 21-24
Author(s):  
Д. З. Маглаев ◽  
А. А. Атаева ◽  
Т. Р. Маглаев ◽  
Х. Ш. Шамсадов
Keyword(s):  
Energy Consumption ◽  
Aqueous Solutions ◽  
Molten Salts ◽  
Minimum Energy ◽  
Redox Process ◽  
Energy Costs ◽  
Minimum Energy Consumption ◽  
Oxide Bronzes ◽  
The One

В данной работе рассматривается окислительно-восстановительный процесс. На конкретных примерах можно подчеркнуть, что из нескольких возможных процессов преимущественно протекает тот, осуществление которого не связано с минимальной затратой энергии. Так же можно, исходя из энергетических затрат, сообщить студентам общие положения процессов на катоде и аноде. This paper deals with the redox process. With specific examples, it can be emphasized that of several possible processes, the one proceeds predominantly, the implementation of which is not associated with a minimum energy consumption. It is also possible to inform students about the general provisions of the processes at the cathode and anode, based on energy costs.

scholarly journals Optimization of Energy-Efficient Speed Profile for Electrified Vehicles

2018 ◽  
Author(s):  
Hadi Abbas ◽  
Youngki Kim ◽  
Jason B. Siegel ◽  
Denise M. Rizzo
Keyword(s):  
Energy Consumption ◽  
Energy Efficient ◽  
Minimum Energy ◽  
Efficient Operation ◽  
Operating Modes ◽  
Minimum Energy Consumption ◽  
System A ◽  
Trip Time ◽  
Route Information

This paper presents a study of energy-efficient operation of vehicles with electrified powertrains leveraging route information, such as road grades, to adjust the speed trajectory. First, Pontryagin’s Maximum Principle (PMP) is applied to derive necessary conditions and to determine the possible operating modes. The analysis shows that only 5 modes are required to achieve minimum energy consumption; full propulsion, cruising, coasting, full regeneration, and full regeneration with conventional braking. The minimum energy consumption problem is reformulated and solved in the distance domain using Dynamic Programming to optimize speed profiles. A case study is shown for a light weight military robot including road grades. For this system, a tradeoff between energy consumption and trip time was found. The optimal cycle uses 20% less energy for the same trip duration, or could reduce the travel time by 14% with the same energy consumption compared to the baseline operation.

scholarly journals A Q-Learning Rescheduling Approach to the Flexible Job Shop Problem Combining Energy and Productivity Objectives

2021 ◽  
Vol 13 (23) ◽  
pp. 13016
Author(s):  
Rami Naimi ◽  
Maroua Nouiri ◽  
Olivier Cardin
Keyword(s):  
Artificial Intelligence ◽  
Energy Consumption ◽  
Job Shop ◽  
Learning Algorithm ◽  
Minimum Energy ◽  
Flexible Job Shop ◽  
Q Learning ◽  
Minimum Energy Consumption ◽  
Machine Failure ◽  
Flexible Job Shop Problem

The flexible job shop problem (FJSP) has been studied in recent decades due to its dynamic and uncertain nature. Responding to a system’s perturbation in an intelligent way and with minimum energy consumption variation is an important matter. Fortunately, thanks to the development of artificial intelligence and machine learning, a lot of researchers are using these new techniques to solve the rescheduling problem in a flexible job shop. Reinforcement learning, which is a popular approach in artificial intelligence, is often used in rescheduling. This article presents a Q-learning rescheduling approach to the flexible job shop problem combining energy and productivity objectives in a context of machine failure. First, a genetic algorithm was adopted to generate the initial predictive schedule, and then rescheduling strategies were developed to handle machine failures. As the system should be capable of reacting quickly to unexpected events, a multi-objective Q-learning algorithm is proposed and trained to select the optimal rescheduling methods that minimize the makespan and the energy consumption variation at the same time. This approach was conducted on benchmark instances to evaluate its performance.

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