scholarly journals Ant Colony Optimized Routing Strategy for Electric Vehicles

2018 ◽  
Vol 2018 ◽  
pp. 1-9 ◽  
Author(s):  
Hyunjin Joo ◽  
Yujin Lim
Keyword(s):  
Energy Efficiency ◽  
Energy Consumption ◽  
Electric Vehicles ◽  
Average Distance ◽  
Average Energy ◽  
Ant Colony ◽  
Energy Efficient Routing ◽  
Conventional Vehicle ◽  
Routing Method ◽  
Routing Methods

Electric vehicles (EVs) have recently attracted increasing research interest, on account of environmental issues and diminishing fuel reserves. EVs are environmentally friendly but have a short driving range. EVs must utilize energy efficiently, because they travel with limited energy. Conventional vehicle routing methods are not suitable for EVs, as they do not take energy consumption into account. This study introduces an energy efficient routing method using ant colony optimization (ER-ACO) to maximize the energy efficiency. We simulated ER-ACO and compared it with other ACO techniques, including the conventional routing method and other approaches for EVs. As a result, the proposed model improved the energy efficiency in terms of both the average distance per kW and average energy consumption.

Reliable and Energy-Efficient Routing Scheme for Underwater Wireless Sensor Networks (UWSNs)

2021 ◽  
Vol 11 (4) ◽  
pp. 42-58
Author(s):  
Semab Iqbal ◽  
Israr Hussain ◽  
Zubair Sharif ◽  
Kamran Hassan Qureshi ◽  
Javeria Jabeen
Keyword(s):  
Energy Efficiency ◽  
Energy Consumption ◽  
Energy Efficient ◽  
Transmission Error ◽  
Wireless Sensor ◽  
Delivery Ratio ◽  
Underwater Communication ◽  
Radio Waves ◽  
Energy Efficient Routing ◽  
Resource Exploration

Despite the fact that the ocean plays a role in everything from the air we breathe to daily weather and climate patterns, we know very little about our ocean. Underwater wireless sensor network (UWSN) is one of the options helping us to discover some domains such as natural assets and underwater resource exploration. However, the acoustic signal is the only suitable option in underwater communication in the absence of radio waves, which face a number of challenges under this environment. To overcome these issues, many routing schemes are introduced by researchers though energy consumption is still a challenge in underwater communication. To overcome the issue of rapid energy consumption, a reliable and energy-efficient routing method is introduced that avoids the redundant forwarding of data; hence, it achieves energy efficiency and eventually prolongs the network lifetime. Simulation results support the claim that the proposed scheme achieves energy efficiency along higher delivery ratio by reducing the data transmission error rate during the routing decisions.

An Energy Aware Routing Based on Swarm Intelligence for Wireless Sensor Networks

2013 ◽  
Vol 706-708 ◽  
pp. 635-638
Author(s):  
Yong Lv
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Swarm Intelligence ◽  
Network Lifetime ◽  
Average Energy ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Energy Aware ◽  
Energy Efficient Routing

Wireless Sensor Networks consisting of nodes with limited power are deployed to collect and distribute useful information from the field to the other sensor nodes. Energy consumption is a key issue in the sensor’s communications since many use battery power, which is limited. In this paper, we describe a novel energy efficient routing approach which combines swarm intelligence, especially the ant colony based meta-heuristic, with a novel variation of reinforcement learning for sensor networks (ARNet). The main goal of our study was to maintain network lifetime at a maximum, while discovering the shortest paths from the source nodes to the sink node using an improved swarm intelligence. ARNet balances the energy consumption of nodes in the network and extends the network lifetime. Simulation results show that compared with the traditional EEABR algorithm can obviously improve adaptability and reduce the average energy consumption effectively.

scholarly journals Optimal Energy Management of Plug-In Hybrid Electric Vehicles Concerning the Entire Lifespan of Lithium-Ion Batteries

Energies ◽  
2020 ◽  
Vol 13 (10) ◽  
pp. 2543 ◽  
Author(s):  
Zeyu Chen ◽  
Jiahuan Lu ◽  
Bo Liu ◽  
Nan Zhou ◽  
Shijie Li
Keyword(s):  
Energy Efficiency ◽  
Energy Consumption ◽  
Lithium Ion Batteries ◽  
Energy Management ◽  
Electric Vehicles ◽  
Hybrid Electric Vehicles ◽  
Lithium Ion ◽  
Energy Management Strategy ◽  
Optimal Energy Management ◽  
Hybrid Electric

The performance of lithium-ion batteries will inevitably degrade during the high frequently charging/discharging load applied in electric vehicles. For hybrid electric vehicles, battery aging not only declines the performance and reliability of the battery itself, but it also affects the whole energy efficiency of the vehicle since the engine has to participate more. Therefore, the energy management strategy is required to be adjusted during the entire lifespan of lithium-ion batteries to maintain the optimality of energy economy. In this study, tests of the battery performances under thirteen different aging stages are involved and a parameters-varying battery model that represents the battery degradation is established. The influences of battery aging on energy consumption of a given plug-in hybrid electric vehicle (PHEV) are analyzed quantitatively. The results indicate that the variations of capacity and internal resistance are the main factors while the polarization and open circuit voltage (OCV) have a minor effect on the energy consumption. Based on the above efforts, the optimal energy management strategy is proposed for optimizing the energy efficiency concerning both the fresh and aging batteries in PHEV. The presented strategy is evaluated by a simulation study with different driving cycles, illustrating that it can balance out some of the harmful effects that battery aging can have on energy efficiency. The energy consumption is reduced by up to 2.24% compared with that under the optimal strategy without considering the battery aging.

Trip Energy Estimation Methodology and Model Based on Real-World Driving Data for Green-Routing Applications

2018 ◽  
Vol 2672 (24) ◽  
pp. 41-48 ◽  
Author(s):  
Jacob Holden ◽  
Harrison Van Til ◽  
Eric Wood ◽  
Lei Zhu ◽  
Jeffrey Gonder ◽  
...  
Keyword(s):  
Energy Consumption ◽  
Fuel Consumption ◽  
Real World ◽  
Energy Use ◽  
Average Energy ◽  
Estimation Model ◽  
Energy Estimation ◽  
Conventional Vehicle ◽  
Look Up Table ◽  
Wide Range

A data-informed model to predict energy use for a proposed vehicle trip has been developed in this paper. The methodology leverages roughly one million miles of real-world driving data to generate the estimation model. Driving is categorized at the sub-trip level by average speed, road gradient, and road network geometry, then aggregated by category. An average energy consumption rate is determined for each category, creating an energy rate look-up table. Proposed vehicle trips are then categorized in the same manner, and estimated energy rates are appended from the look-up table. The methodology is robust and applicable to a wide range of driving data. The model has been trained on vehicle travel profiles from the Transportation Secure Data Center at the National Renewable Energy Laboratory and validated against on-road fuel consumption data from testing in Phoenix, Arizona. When compared against the detailed on-road conventional vehicle fuel consumption test data, the energy estimation model accurately predicted which route would consume less fuel over a dozen different tests. When compared against a larger set of real-world origin–destination pairs, it is estimated that implementing the present methodology should accurately select the route that consumes the least fuel 90% of the time. The model results can be used to inform control strategies in routing tools, such as change in departure time, alternate routing, and alternate destinations to reduce energy consumption. This work provides a highly extensible framework that allows the model to be tuned to a specific driver or vehicle type.

scholarly journals Enhancing Energy Efficiency of Wireless Sensor Network through the Design of Energy Efficient Routing Protocol

2016 ◽  
Vol 2016 ◽  
pp. 1-16 ◽  
Author(s):  
Noor Zaman ◽  
Low Tang Jung ◽  
Muhammad Mehboob Yasin
Keyword(s):  
Energy Efficiency ◽  
Energy Consumption ◽  
Wireless Sensor Network ◽  
Sensor Network ◽  
Routing Protocol ◽  
Energy Efficient ◽  
Wireless Sensor ◽  
Cross Layer Design ◽  
Energy Efficient Routing ◽  
Overall Performance

Wireless Sensor Network (WSN) is known to be a highly resource constrained class of network where energy consumption is one of the prime concerns. In this research, a cross layer design methodology was adopted to design an energy efficient routing protocol entitled “Position Responsive Routing Protocol” (PRRP). PRRP is designed to minimize energy consumed in each node by (1) reducing the amount of time in which a sensor node is in an idle listening state and (2) reducing the average communication distance over the network. The performance of the proposed PRRP was critically evaluated in the context of network lifetime, throughput, and energy consumption of the network per individual basis and per data packet basis. The research results were analyzed and benchmarked against the well-known LEACH and CELRP protocols. The outcomes show a significant improvement in the WSN in terms of energy efficiency and the overall performance of WSN.

A Voronoi- Ant Colony based Routing (VoR-Ant-R) Algorithm for WMSNs

2022 ◽  
Vol 13 (2) ◽  
pp. 0-0
Keyword(s):  
Energy Efficiency ◽  
Energy Consumption ◽  
Ant Colony ◽  
Delivery Ratio ◽  
Wireless Multimedia ◽  
Energy Hole ◽  
Packet Delivery ◽  
Multimedia Sensor Networks ◽  
Increase Energy Efficiency ◽  
Simulation Results

Wireless Multimedia Sensor Networks (WMSNs) have been used in many applications and powerful distributed systems. But the performance of WMSNs is suffering from the occurrence of energy holes. To improve the performance of the network and packet delivery ratio, a Voronoi-Ant colony based Routing (VoR-Ant-R) algorithm is proposed for WMSNs to discover the energy holes and finds the shortest path from the source to destination in the WMSNs even though faces some obstacles. The WMSNs are constructed using the Voronoi structure to bypass energy holes. After bypassing the energy hole in the path; an ACO is introduced to select a neighborhood node for data forwarding. This ACO constructs the shortest optimized path to enhance the performance of the WMSNs. The proposed work is experimentally compared with other algorithms such as IEEABR, EEABR, SC, and BEES. The simulation results show that VoR-Ant-R can increase energy efficiency, success rate, reduces energy consumption, and latency.

scholarly journals Differences in Energy Consumption in Electric Vehicles: An Exploratory Real-World Study in Beijing

2017 ◽  
Vol 2017 ◽  
pp. 1-17 ◽  
Author(s):  
Kezhen Hu ◽  
Jianping Wu ◽  
Tim Schwanen
Keyword(s):  
Energy Efficiency ◽  
Energy Consumption ◽  
Electric Vehicles ◽  
Real World ◽  
Time Series Data ◽  
Urban Traffic ◽  
Environmental Benefits ◽  
Series Data ◽  
Traffic Conditions ◽  
Infrastructure Design

Electric vehicles (EVs) are widely regarded as a promising solution to reduce air pollution in cities and key to a low carbon mobility future. However, their environmental benefits depend on the temporal and spatial context of actual usage (journey energy efficiency) and the rolling out of EVs is complicated by issues such as limited range. This paper explores how the energy efficiency of EVs is affected and shaped by driving behavior, personal driving styles, traffic conditions, and infrastructure design in the real world. Tests have been conducted with a Nissan LEAF under a typical driving cycle on the Beijing road network in order to improve understanding of variations in energy efficiency among drivers under different urban traffic conditions. Energy consumption and operation parameters were recorded in both peak and off-peak hours for a total of 13 drivers. The analysis reported in this paper shows that there are clear patterns in energy consumption along a route that are in part related to differences in infrastructure design, traffic conditions, and personal driving styles. The proposed method for analyzing time series data about energy consumption along routes can be used for research with larger fleets of EVs in the future.

scholarly journals Contribution of Driving Efficiency and Vehicle-to-Grid to Eco-Design

Energies ◽  
2020 ◽  
Vol 13 (15) ◽  
pp. 3997
Author(s):  
David Borge-Diez ◽  
Pedro Miguel Ortega-Cabezas ◽  
Antonio Colmenar-Santos ◽  
Jorge-Juan Blanes-Peiró
Keyword(s):  
Energy Efficiency ◽  
Energy Consumption ◽  
Product Design ◽  
Design Process ◽  
Electric Vehicles ◽  
Raw Materials ◽  
Manufacturing Processes ◽  
Vehicle To Grid ◽  
Improve Energy Efficiency ◽  
Reduction Of Energy Consumption

Designing eco-friendly products involves energy efficiency improvements. Eco-friendly products must consider not only raw materials and manufacturing processes to improve energy efficiency but also energy needed when designing them. This research shows how eco-routing (ER), eco-charging (EC), eco-driving (EDR), vehicle-to-grid (V2G) and electric vehicles (EVs) can contribute to the reduction of energy consumption during product design. To do this, a group of 44 engineers assigned to the project was chosen to assess the total energy available for V2G when driving EVs from their homes to the design center by using ER, ED and EC by running an application coded by the authors. The energy stored in EVs was used to quantify the reduction in energy consumption of the buildings present in the design center. The results show that the energy saving ranges from 2.89% to 6.9% per day—in other words, 93 kWh per day during the design process. In addition, the fact of making the design process greener implies that renewable energies (REs) are integrated better during the design process. By running the application, drivers are informed about the RE mix when the charging process takes place. Finally, this research shows that current policies make V2G and vehicle-to-home techniques not compatible.

Sign in / Sign up

Export Citation Format

Share Document