Optimizing Energy Supply for Full Electric Vehicles in Smart Cities: A Comprehensive Mobility Network Model DOI Creative Commons
Víctor Fernández Pallarés, Virgilio Pérez, Rosa Roig

et al.

World Electric Vehicle Journal, Journal Year: 2024, Volume and Issue: 16(1), P. 5 - 5

Published: Dec. 27, 2024

The integration of Full Electric Vehicles (FEVs) into the smart city ecosystem is an essential step towards achieving sustainable urban mobility. This study presents a comprehensive mobility network model designed to predict and optimize energy supply for FEVs within cities. integrates advanced components such as Charge Station Control Center (CSCC), charging infrastructure, dynamic user interface. Important aspects include analyzing power consumption, forecasting demand, monitoring State (SoC) FEV batteries using innovative algorithms validated through real-world applications in Valencia (Spain) Ljubljana (Slovenia). Results indicate high accuracies SoC tracking (error < 0.05%) demand (MSE ~6 × 10−4), demonstrating model’s reliability adaptability across diverse environments. research contributes development resilient, efficient, frameworks, emphasizing real-time data-driven decision-making management.

Language: Английский

Strategies for Workplace EV Charging Management DOI Creative Commons
Natascia Andrenacci, Antonino Genovese,

Giancarlo Giuli

et al.

Energies, Journal Year: 2025, Volume and Issue: 18(2), P. 421 - 421

Published: Jan. 19, 2025

Electric vehicles (EVs) help reduce transportation emissions. A user-friendly charging infrastructure and efficient processes can promote their wider adoption. Low-power is effective for short-distance travel, especially when are parked extended periods, like during daily commutes. These idle times present opportunities to improve coordination between EVs service providers meet needs. The study examines strategies coordinated in workplace parking lots minimize the impact on power grid while maximizing satisfaction of demand. Our method utilizes a heuristic approach EV charging, focusing event logic that considers arrival departure energy requirements. We compare various management methods lot against first-in-first-out (FIFO) strategy. Using real data usage, found electric vehicle be achieved either through optimized scheduling with single high-power charger, requiring user cooperation, or by installing multiple chargers alternating sockets. Compared FIFO implemented allow reduction maximum 30 40%, demand rate 99%, minimum SOC amount 83%.

Language: Английский

Citations

0
User Cost Minimization and Load Balancing for Multiple Electric Vehicle Charging Stations Based on Deep Reinforcement Learning DOI Creative Commons
Yongxiang Xia, Zhongyi Cheng, Jiaqi Zhang

et al.

World Electric Vehicle Journal, Journal Year: 2025, Volume and Issue: 16(3), P. 184 - 184

Published: March 19, 2025

In the context of global energy conservation and emission reduction, electric vehicles (EVs) are essential for low-carbon transport. However, their rapid growth challenges power grids with load imbalances across networks increases user charging costs. To address issues balancing large-scale distribution costs users, this paper proposes an optimization strategy EV behavior based on deep reinforcement learning (DRL). The aims to minimize while achieving networks. Specifically, divides process into two stages: station selection in-station scheduling. first stage, a Load Balancing Matching Strategy (LBMS) is employed assist users in selecting station. second we use DRL algorithm. algorithm, design novel reward function that enables stations meet demands minimizing reducing gap among Case study results demonstrate effectiveness proposed multi-distribution network environment. Moreover, even when faced varying levels participation, continues strong performance.

Language: Английский

Citations

0
Research on Actuator Control System Based on Improved MPC DOI Creative Commons
Qingjian Zhao, Q. Zhang, Shuang Zhao

et al.

Actuators, Journal Year: 2025, Volume and Issue: 14(6), P. 263 - 263

Published: May 27, 2025

To improve the control accuracy and interference resistance of actuator systems in complex environments, a complete system solution has been designed. The uses an STM32 controller as core processing unit, integrating high-precision position sensors to build multi-level architecture. An improved model predictive algorithm is proposed, which introduces extended state observers multi-objective optimization strategies estimate states external disturbances real-time, achieving precise disturbance compensation. Experimental test results show that, under electromagnetic mechanical vibration conditions, system’s stability robustness are significantly enhanced, with error fluctuations less than 0.03 mm, dynamic response time 4.82 s, overshoot 1.5%, steady-state 0.14 energy consumption reduced by 15%, all better MPC, fuzzy control, PID methods similar conditions. This research provides comprehensive for hardware design industrial automation precision manufacturing.

Language: Английский

Citations

0
CONTESTED SPACES: BUSINESS MODEL TENSIONS AND CONTROL CHALLENGES IN INDUSTRY-CONVERGING ECOSYSTEMS DOI
Rami Darwish, Mats Magnusson, Gunilla Ölundh Sandström

et al.

International Journal of Innovation Management, Journal Year: 2025, Volume and Issue: unknown

Published: May 27, 2025

The transportation sector is undergoing a significant shift towards electrification, driven by sustainability challenges and battery electric vehicle (BEV) technology advancements. This transition also leads to convergence of transport energy industries, introducing new dynamics creating business opportunities in these sectors. Such changes have extensive implications not only for single firms but entire ecosystems as adapt technologies, activities, models. study introduces the concept Industry-Converging Ecosystems, where traditional industrial boundaries become less distinct, requiring collaboration among unfamiliar participants across various industries. paper investigates tensions between value creation capture control such through case an innovative charging system buses Västerås, Sweden. findings advance ecosystem research (1) industry-converging concept, (2) revealing two sources model stemming from monetisation uncertainties resource competition, (3) demonstrating lack clarity caused limited influence over models diminished legitimacy due their newness.

Language: Английский

Citations

0
Optimization of Solar Generation and Battery Storage for Electric Vehicle Charging with Demand-Side Management Strategies DOI Creative Commons
C. Berna, Lucas Álvarez-Piñeiro, David Blanco

et al.

World Electric Vehicle Journal, Journal Year: 2025, Volume and Issue: 16(6), P. 312 - 312

Published: June 3, 2025

The integration of Electric Vehicles (EVs) with solar power generation is important for decarbonizing the economy. While electrifying transportation reduces Greenhouse Gas (GHG) emissions, its success depends on ensuring that EVs are charged clean energy, requiring significant increases in photovoltaic capacity and robust Demand-Side Management (DSM) solutions. EV charging patterns, such as home, workplace, public charging, need adapted strategies to match generation. This study analyzes a system designed meet unitary hourly average energy demand (8760 MWh annually) using an optimization framework balances PV battery storage ensure reliable supply. Historical data from 22 years used analyze seasonal interannual fluctuations. results show alone can cover around 30% without DSM, rising nearly 50% aggressive DSM measures, capacities 1.0–2.0 MW. reveals incorporating achieve near 100% coverage 8.0–9.0 Moreover, required 18 about 10 MWh. These findings highlight importance integrating optimization-based management enhance efficiency cost-effectiveness, offering pathway toward more sustainable resilient infrastructure.

Language: Английский

Citations

0
A New Approach to Interoperability within the Smart City Based on Time Series-Embedded Adaptive Traffic Prediction Modelling DOI
Víctor Fernández, Virgilio Pérez

Networks and Spatial Economics, Journal Year: 2024, Volume and Issue: unknown

Published: Nov. 25, 2024

Language: Английский

Citations

2
Utilizing Graphite Waste from the Acheson Furnace as Anode Material in Lithium-Ion Batteries DOI Creative Commons
Inchan Yang, Sung‐Deuk Choi, Sangwook Kim

et al.

Applied Sciences, Journal Year: 2024, Volume and Issue: 14(23), P. 11353 - 11353

Published: Dec. 5, 2024

This study investigates the potential of graphite waste (GW) from Acheson furnace as a sustainable and cost-effective anode material for lithium-ion batteries (LIBs). Conventional materials face challenges such energy-intensive production processes reliance on virgin resources, leading to high costs environmental concerns. GW furnace, which already possesses carbon purity (98.5%–99.9%) crystallinity (93.5%), offers promising alternative by eliminating need graphitization extensive purification. Through spheronization coating, was successfully optimized achieve electrochemical properties comparable commercial (CAM), including an initial Coulombic efficiency 85.1% specific capacity 348.9 mAh/g. These findings suggest that represents viable pathway toward environmentally friendly LIB anodes.

Language: Английский

Citations

0
Optimizing Energy Supply for Full Electric Vehicles in Smart Cities: A Comprehensive Mobility Network Model DOI Creative Commons
Víctor Fernández Pallarés, Virgilio Pérez, Rosa Roig

et al.

World Electric Vehicle Journal, Journal Year: 2024, Volume and Issue: 16(1), P. 5 - 5

Published: Dec. 27, 2024

The integration of Full Electric Vehicles (FEVs) into the smart city ecosystem is an essential step towards achieving sustainable urban mobility. This study presents a comprehensive mobility network model designed to predict and optimize energy supply for FEVs within cities. integrates advanced components such as Charge Station Control Center (CSCC), charging infrastructure, dynamic user interface. Important aspects include analyzing power consumption, forecasting demand, monitoring State (SoC) FEV batteries using innovative algorithms validated through real-world applications in Valencia (Spain) Ljubljana (Slovenia). Results indicate high accuracies SoC tracking (error < 0.05%) demand (MSE ~6 × 10−4), demonstrating model’s reliability adaptability across diverse environments. research contributes development resilient, efficient, frameworks, emphasizing real-time data-driven decision-making management.

Language: Английский

Citations

0