scholarly journals Energy Optimization of Electric Vehicles by Distributing Driving Power Considering System State Changes

Energies ◽  
2021 ◽  
Vol 14 (3) ◽  
pp. 594
Author(s):  
In-Gyu Jang ◽  
Chung-Seong Lee ◽  
Sung-Ho Hwang
Keyword(s):  
Uniform Distribution ◽  
Electric Vehicle ◽  
Driving Forces ◽  
Optimization Method ◽  
System Operation ◽  
Distribution Method ◽  
Operation Efficiency ◽  
Input Terminal ◽  
Voltage Change ◽  
Terminal Voltage

In a battery-electric vehicle, a representative electric vehicle, there is a growing demand for performance and one-charge mileage improvement. As an alternative to such improvements, the capacity of the battery has been increased; however, due to the corresponding increase in the weight of the battery and the limited space in the vehicle, increasing the capacity of the battery also has limitations. Therefore, researches are being actively conducted to improve system operation efficiency to overcome such limitations. This paper proposes a distributing method of the driving forces to a battery-powered electric shuttle bus for last-mile mobility equipped with the decentralized driving system while taking into account voltage changes of the input terminals due to changes in the battery charge. The system operation efficiency changes were compared and evaluated by performing energy consumption analysis using ‘Manhattan Bus Driving Cycle’ at low voltage condition (SOC 20%). Various analyzes were performed and compared, such as the uniform distribution method of driving forces of the front and rear wheels (Uniform), the optimization method without considering the input terminal voltage change (Vnorm = 90 V), and the optimization method considering the input terminal voltage change (Vdclink). As a result, it shows that the proposed algorithm can improve 6.0% compared to the conventional uniform driving force distribution method (Uniform). Moreover, it shows that the real-time optimization method without considering the input voltage change (Vnorm = 90 V) can improve 5.3% compared to the uniform distribution method. The proposed method can obtain an additional 0.7% increase in total cost compared to the existing optimization method, which shows that the vehicle system has cost-effectiveness by reducing the battery capacity required to achieve the same mileage.

Simulation-Based Hybrid Optimization Method for the Digital Twin of Garment Production Lines

2021 ◽  
Vol 21 (3) ◽  
Author(s):  
Woo-Kyun Jung ◽  
Young-Chul Park ◽  
Jae-Won Lee ◽  
Eun Suk Suh
Keyword(s):  
Expert Knowledge ◽  
Structural Characteristics ◽  
Optimization Method ◽  
Hybrid Optimization ◽  
Optimization Process ◽  
Production Lines ◽  
Distribution Method ◽  
Workload Analysis ◽  
Hybrid Optimization Method ◽  
Simulation Based

AbstractImplementing digital transformation in the garment industry is very difficult, owing to its labor-intensive structural characteristics. Further, the productivity of a garment production system is considerably influenced by a combination of processes and operators. This study proposes a simulation-based hybrid optimization method to maximize the productivity of a garment production line. The simulation reflects the actual site characteristics, i.e., process and operator level indices, and the optimization process reflects constraints based on expert knowledge. The optimization process derives an optimal operator sequence through a genetic algorithm (GA) and sequentially removes bottlenecks through workload analysis based on the results. The proposed simulation optimization (SO) method improved productivity by ∼67.4%, which is 52.3% higher than that obtained by the existing meta-heuristic algorithm. The correlation between workload and production was verified by analyzing the workload change trends. This study holds significance because it presents a new simulation-based optimization model that further applies the workload distribution method by eliminating bottlenecks and digitizing garment production lines.

scholarly journals Optimization of Disassembly Strategies for Electric Vehicle Batteries

Batteries ◽  
2021 ◽  
Vol 7 (4) ◽  
pp. 74
Author(s):  
Sabri Baazouzi ◽  
Felix Paul Rist ◽  
Max Weeber ◽  
Kai Peter Birke
Keyword(s):  
Electric Vehicle ◽  
Circular Economy ◽  
Optimization Method ◽  
Sustainable Mobility ◽  
Component Level ◽  
Battery System ◽  
Safety Risks ◽  
Disassembly Sequence ◽  
Resource Intensity ◽  
Automated Disassembly

Various studies show that electrification, integrated into a circular economy, is crucial to reach sustainable mobility solutions. In this context, the circular use of electric vehicle batteries (EVBs) is particularly relevant because of the resource intensity during manufacturing. After reaching the end-of-life phase, EVBs can be subjected to various circular economy strategies, all of which require the previous disassembly. Today, disassembly is carried out manually and represents a bottleneck process. At the same time, extremely high return volumes have been forecast for the next few years, and manual disassembly is associated with safety risks. That is why automated disassembly is identified as being a key enabler of highly efficient circularity. However, several challenges need to be addressed to ensure secure, economic, and ecological disassembly processes. One of these is ensuring that optimal disassembly strategies are determined, considering the uncertainties during disassembly. This paper introduces our design for an adaptive disassembly planner with an integrated disassembly strategy optimizer. Furthermore, we present our optimization method for obtaining optimal disassembly strategies as a combination of three decisions: (1) the optimal disassembly sequence, (2) the optimal disassembly depth, and (3) the optimal circular economy strategy at the component level. Finally, we apply the proposed method to derive optimal disassembly strategies for one selected battery system for two condition scenarios. The results show that the optimization of disassembly strategies must also be used as a tool in the design phase of battery systems to boost the disassembly automation and thus contribute to achieving profitable circular economy solutions for EVBs.

Micro-Grid Energy Optimization Include Battery-Swapping-Station

2014 ◽  
Vol 672-674 ◽  
pp. 1358-1363
Author(s):  
Liu Shu ◽  
Fang Liu ◽  
Xiu Yang
Keyword(s):  
Genetic Algorithm ◽  
Renewable Energy ◽  
Electric Vehicle ◽  
Negative Impact ◽  
Operating Cost ◽  
Energy Optimization ◽  
Optimal Operation ◽  
Operation Efficiency ◽  
Micro Grid ◽  
Minimum Operating

Accessing electric vehicle (EV) into micro-grid (MG) by battery-swapping station (BSS) will not only reduce the negative impact brought by EVs which are directly accessed into MG, but also improve the capacity of MG to absorb more renewable energy. That BSS is regarded as schedulable load is guided to avoid peak and fill valley according to TOU. As a result, the gap between peak and valley of MG is decreased and the operation efficiency of MG is elevated. A specific MG is taken as the studying object and the minimum operating cost is regarded as the optimizing goal, then the genetic algorithm is used to optimize the outputting of each micro-source and the charging power of BSS so that the optimal operation is realized.

A general trajectory optimization method for aircraft taxiing on flight deck of carrier

2018 ◽  
Vol 233 (4) ◽  
pp. 1340-1353 ◽  
Author(s):  
Yu Wu ◽  
Ning Hu ◽  
Xiangju Qu
Keyword(s):  
Optimization Algorithm ◽  
Trajectory Optimization ◽  
Fitness Function ◽  
Control Variable ◽  
Optimization Method ◽  
Operation Efficiency ◽  
Ground Motion Model ◽  
Aircraft System ◽  
Chicken Swarm Optimization ◽  
Flight Deck

Enhancing operation efficiency of flight deck has become a hotspot because it has an important impact on the fighting capacity of the carrier–aircraft system. To improve the operation efficiency, aircraft need taxi to the destination on deck with the optimal trajectory. In this paper, a general method is proposed to solve the trajectory optimization problem for aircraft taxiing on flight deck considering that the existing methods can only deal with the problem in some specific cases. Firstly, the ground motion model of aircraft, the collision detection strategy and the constraints are included in the mathematical model. Then the principles of the chicken swarm optimization algorithm and the generality of the proposed method are explained. In the trajectory optimization algorithm, several strategies, i.e. generation of collocation points, transformation of control variable, and setting of segmented fitness function, are developed to meet the terminal constraints easier and make the search efficient. Three groups of experiments with different environments are conducted. Aircraft with different initial states can reach the targets with the minimum taxiing time, and the taxiing trajectories meet all the constraints. The reason why the general trajectory optimization method is validated in all kinds of situations is also explained.

scholarly journals Optimal Operation of Isolated Microgrids Considering Frequency Constraints

2019 ◽  
Vol 9 (2) ◽  
pp. 223 ◽  
Author(s):  
Josep-Andreu Vidal-Clos ◽  
Eduard Bullich-Massagué ◽  
Mònica Aragüés-Peñalba ◽  
Guillem Vinyals-Canal ◽  
Cristian Chillón-Antón ◽  
...  
Keyword(s):  
Optimization Problem ◽  
Maximum Load ◽  
Optimization Method ◽  
Optimal Operation ◽  
System Operation ◽  
Frequency Constraints ◽  
Autonomous Operation ◽  
Frequency Constraint ◽  
Photovoltaic Power ◽  
Pv Generation

Isolated microgrids must be able to perform autonomous operation without external grid support. This leads to a challenge when non-dispatchable generators are installed because power imbalances can produce frequency excursions compromising the system operation. This paper addresses the optimal operation of PV–battery–diesel-based microgrids taking into account the frequency constraints. Particularly, a new stochastic optimization method to maximize the PV generation while ensuring the grid frequency limits is proposed. The optimization problem was formulated including a minimum frequency constraint, which was obtained from a dynamic study considering maximum load and photovoltaic power variations. Once the optimization problem was formulated, three complete days were simulated to verify the proper behavior. Finally, the system was validated in a laboratory-scaled microgrid.

scholarly journals Current Distribution Method of Induction Motor for Electric Vehicle in Whole Speed Range Based on Gaussian Process

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 165974-165984 ◽  
Author(s):  
Fang Xie ◽  
Wenjie Hong ◽  
Wenming Wu ◽  
Kangkang Liang ◽  
Chenming Qiu
Keyword(s):  
Gaussian Process ◽  
Induction Motor ◽  
Electric Vehicle ◽  
Current Distribution ◽  
Distribution Method ◽  
Speed Range
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