scholarly journals Packet-based nonlinear battery energy consumption optimizing for WSNs nodes

2014 ◽  
Vol 11 (9) ◽  
pp. 20140167-20140167 ◽  
Author(s):  
Rui Hou ◽  
Mingming Zheng
Keyword(s):  
Energy Consumption ◽  
Battery Energy

scholarly journals Improving the Autonomy of a Mid-Drive Motor Electric Bicycle Based on System Efficiency Maps and Its Performance

2021 ◽  
Vol 12 (2) ◽  
pp. 59
Author(s):  
Ivan Arango ◽  
Carlos Lopez ◽  
Alejandro Ceren
Keyword(s):  
Energy Consumption ◽  
Management Strategy ◽  
Computational Analysis ◽  
Experimental Models ◽  
System Efficiency ◽  
Drive Motor ◽  
Electric Bicycle ◽  
Chain Transmission ◽  
Battery Energy ◽  
Efficiency Map

Around the world, the e-bike has evolved from a recreational and sports object to an increasingly used means of transportation. Due to this, improving aspects such as range and energy efficiency has become very relevant. This article presents experimental models for the components’ efficiency of a mid-drive motor e-bike (charger; battery; and controller, motor, and reduction gears subsystem), and integrates them with previously elaborated models for the chain transmission system, thus generating an overall efficiency map of the e-bike. The range of the electric bicycle is analyzed by integrating the efficiency map of the system and its performance mathematical model, aiming to determine the per unit of distance battery energy consumption. The above-mentioned calculations are applied to develop a management strategy that can determine the optimal assistance level and chain transmission ratio, maximizing range and leaving speed unaffected. The driving strategy was compared against other driving techniques using computational analysis, this allowed for the observation of the proposed strategy improving the system’s range by reducing the battery energy consumption.

scholarly journals 1 DESIGN OF MODULAR ARCHITECTURE FOR EV AND HEV FOR PASSENGER CARS

2021 ◽  
Author(s):  
Midhun Muraleedharan ◽  
◽  
Amitabh Das ◽  
Dr. Mohammad Rafiq Agrewale ◽  
Dr. K.C. Vora ◽  
...  
Keyword(s):  
Neural Network ◽  
Energy Consumption ◽  
Fuel Consumption ◽  
Modular Architecture ◽  
Passenger Cars ◽  
Passenger Car ◽  
Vehicle Performance ◽  
Matlab Simulink ◽  
System Designer ◽  
Battery Energy

Hybridization is important to obtain the advantages of both the engine and motor as the sources of propulsion. This paper discusses the effect of hybridization of powertrain on vehicle performance. The Hybrid architectures are differentiated on the basis percentage of power dependency on the engine and motor. Passenger car with hybridization ratios of 20%, 40%, 60%, 80% and 100% are modelled on MATLAB/Simulink using the backward facing approach with the engine and motor specifications remaining constant. The hybridizations ratios and the energy consumption in terms of fuel and battery energy are obtained from the model and compared. Neural network is implemented to determine the fuel consumption. The outputs can be used by a system designer to determine a desirable hybridization factor based on the requirements dictated by the specific application.

On Balancing Energy Consumption, Rendering Speed, and Image Quality on Mobile Devices

2012 ◽  
pp. 231-250
Author(s):  
Fan Wu ◽  
Emmanuel Agu ◽  
Clifford Lindsay ◽  
Chung-han Chen
Keyword(s):  
Energy Consumption ◽  
Image Quality ◽  
Mobile Devices ◽  
Time Frame ◽  
Operating Conditions ◽  
Mobile Graphics ◽  
Balancing Energy ◽  
Interactive Frame ◽  
Battery Energy ◽  
Predict Model

Mobile games and graphics are popular because un-tethered computing is convenient and ubiquitous entertainment is compelling. However, rendering graphics on mobile devices faces challenges due to limited system resources, such as battery energy, and low memory and disk space. Real time frame rates, low energy consumption and high image quality are all desirable attributes of interactive mobile graphics; however, achieving these objectives is conflicting. For instance, increasing mesh resolutions improves rendered image quality but consumes more battery energy. Therefore, the authors propose a mobile graphics heuristic to minimize energy consumption while maintaining acceptable image quality and interactive frame rates. Over the lifetime of a mobile graphics application, scene complexity, animation paths, user interactivity and other elements all change its CPU and resource demands. In this regard, a heuristic that dynamically changes scene mesh LoDs and amount of CPU timeslices allotted to the mobile graphics application is presented to select optimal operating conditions that balance rendering speed, energy conservation and image quality. Additionally, a workload predict model is proposed so that the heuristic can monitor both application workload and the availability of resources of mobile devices periodically, while adaptively determining how much resources will be allocated to applications.

An Efficient Sleeping Scheduling for Save Energy Consumption in Wireless Sensor Networks

2013 ◽  
Vol 756-759 ◽  
pp. 2288-2293
Author(s):  
Shu Guang Jia ◽  
Li Peng Lu ◽  
Ling Dong Su ◽  
Gui Lan Xing ◽  
Ming Yue Zhai
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Smart Grid ◽  
Round Robin ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Active Sensors ◽  
Save Energy ◽  
Battery Energy

Smart grid has become one hot topic at home and abroad in recent years. Wireless Sensor Networks (WSNs) has applied to lots of fields of smart grid, such as monitoring and controlling. We should ensure that there are enough active sensors to satisfy the service request. But, the sensor nodes have limited battery energy, so, how to reduce energy consumption in WSNs is a key challenging. Based on this problem, we propose a sleeping scheduling model. In this model, firstly, the sensor nodes round robin is used to let as little as possible active nodes while all the targets in the power grid are monitored; Secondly, for removing the redundant active nodes, the sensor nodes round robin is further optimized. Simulation result indicates that this sleep mechanism can save the energy consumption of every sensor node.

An Efficient Sleeping Scheduling for Saving Energy Consumption in Wireless Sensor Networks

2012 ◽  
Vol 229-231 ◽  
pp. 1261-1264
Author(s):  
Li Peng Lu ◽  
Ming Yue Zhai ◽  
Ying Liu ◽  
Xiao Da Sun
Keyword(s):  
Mathematical Model ◽  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Smart Grid ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Reduce Energy Consumption ◽  
Battery Energy ◽  
Sleep Mechanism

Wireless Sensor Networks (WSNs) has been widely recognized as a promising technology in smart grid. However, sensor nodes have limited battery energy. So, we present a mathematical model which is to reduce energy consumption and prolong the lifetime of WSNs. Because of the high density of sensor nodes deployment, a sleep mechanism is proposed to make all sensor nodes work by turns while all service requests can be satisfied. And then, an Improved Sleep Mechanism is put forward to remove redundant active nodes. The simulation result indicates that energy consumption adopting the ISNSS is lower than or equal to the energy consumption adopting SNSS. The SNSS and ISNSS all can save some energy of WSNs to some extent and when the redundant active nodes are removed, the network energy consumption is further reduced based on the SNSS.

On Balancing Energy Consumption, Rendering Speed, and Image Quality on Mobile Devices

2010 ◽  
Vol 1 (3) ◽  
pp. 51-71
Author(s):  
Fan Wu ◽  
Emmanuel Agu ◽  
Clifford Lindsay ◽  
Chung-han Chen
Keyword(s):  
Energy Consumption ◽  
Image Quality ◽  
Mobile Devices ◽  
Time Frame ◽  
Operating Conditions ◽  
Mobile Graphics ◽  
Balancing Energy ◽  
Interactive Frame ◽  
Battery Energy ◽  
Predict Model

Mobile games and graphics are popular because un-tethered computing is convenient and ubiquitous entertainment is compelling. However, rendering graphics on mobile devices faces challenges due to limited system resources, such as battery energy, and low memory and disk space. Real time frame rates, low energy consumption and high image quality are all desirable attributes of interactive mobile graphics; however, achieving these objectives is conflicting. For instance, increasing mesh resolutions improves rendered image quality but consumes more battery energy. Therefore, the authors propose a mobile graphics heuristic to minimize energy consumption while maintaining acceptable image quality and interactive frame rates. Over the lifetime of a mobile graphics application, scene complexity, animation paths, user interactivity and other elements all change its CPU and resource demands. In this regard, a heuristic that dynamically changes scene mesh LoDs and amount of CPU timeslices allotted to the mobile graphics application is presented to select optimal operating conditions that balance rendering speed, energy conservation and image quality. Additionally, a workload predict model is proposed so that the heuristic can monitor both application workload and the availability of resources of mobile devices periodically, while adaptively determining how much resources will be allocated to applications.

scholarly journals A Robust and Energy-Efficient Weighted Clustering Algorithm on Mobile Ad Hoc Sensor Networks †

Algorithms ◽  
2018 ◽  
Vol 11 (8) ◽  
pp. 116 ◽  
Author(s):  
Huamei Qi ◽  
Fengqi Liu ◽  
Tailong Xiao ◽  
Jiang Su
Keyword(s):  
Energy Consumption ◽  
Energy Efficient ◽  
Clustering Algorithm ◽  
Ad Hoc ◽  
Cluster Head ◽  
Detection Algorithm ◽  
Residual Energy ◽  
Weighted Clustering ◽  
Distributed Fault Detection ◽  
Battery Energy

In an Ad hoc sensor network, nodes have characteristics of limited battery energy, self-organization and low mobility. Due to the mobility and heterogeneity of the energy consumption in the hierarchical network, the cluster head and topology are changed dynamically. Therefore, topology control and energy consumption are growing to be critical in enhancing the stability and prolonging the lifetime of the network. In order to improve the survivability of Ad hoc network effectively, this paper proposes a new algorithm named the robust, energy-efficient weighted clustering algorithm (RE2WCA). For the homogeneous of the energy consumption; the proposed clustering algorithm takes the residual energy and group mobility into consideration by restricting minimum iteration times. In addition, a distributed fault detection algorithm and cluster head backup mechanism are presented to achieve the periodic and real-time topology maintenance to enhance the robustness of the network. The network is analyzed and the simulations are performed to compare the performance of this new clustering algorithm with the similar algorithms in terms of cluster characteristics, lifetime, throughput and energy consumption of the network. The result shows that the proposed algorithm provides better performance than others.

scholarly journals Smart Sensing Period for Efficient Energy Consumption in IoT Network

Sensors ◽  
2019 ◽  
Vol 19 (22) ◽  
pp. 4915
Author(s):  
Woojae Kim ◽  
Inbum Jung
Keyword(s):  
Energy Consumption ◽  
Back Propagation ◽  
Back Propagation Neural Network ◽  
Sensors And Actuators ◽  
Target Time ◽  
Efficient Energy ◽  
Battery Power ◽  
Consumption Rates ◽  
Smart Sensing ◽  
Battery Energy

The devices included in IoT networks have sensors and actuators for monitoring their surroundings. These operate on battery energy, according to the characteristics of the environment in which they are deployed. To enhance the longevity of IoT networks, the devices need to avoid any unnecessary sensing operations in order to reduce the power consumption rate. However, as existing sensing methods use a fixed sensing period policy, battery power wastage is inevitable. In this paper, a smart sensing period policy is proposed for efficient energy consumption in an IoT network. The proposed method uses a learning model based on a back-propagation neural network. Within the target time, it can efficiently use the battery energy without any surplus or wastage in the quantity of preserved battery energy. In experiments, our proposed method shows improved results in battery energy consumption rates compared to the existing sensing period methods.

scholarly journals Combined Energy and Process Simulation to Foster Efficiency in Non-automated Material Handling System Design

2015 ◽  
Vol 3 (1) ◽  
pp. 28
Author(s):  
Patrick Fekete ◽  
Sirirat Lim ◽  
Steve Martin ◽  
Katja Kuhn ◽  
Nick Wright
Keyword(s):  
Energy Consumption ◽  
Material Handling ◽  
Data Generation ◽  
Material Handling System ◽  
System Efficiency ◽  
Handling System ◽  
Automated Material Handling System ◽  
Novel Approach ◽  
Automated Material Handling ◽  
Battery Energy

Energy and resource efficiency are becoming more and more important objectives in industrial companies, so that it has also become relevant to material handling as part of the lean strategy in supply chain management. The design of sustainable, energy efficient material handling systems and processes depends on methods and tools that analyse and evaluate the composition of the technologies and processes of the system. Therefore analysis on detailed data on energy consumption, energy supply and process organisation is required to improve overall system efficiency. This study proposes a novel approach to energy data generation based on Standardised Energy Consuming Activities (SECA). Simulating process energy consumption and consumption behaviour based on process function investigations increases knowledge about the sequence and characteristics of energy consumption and its process allocation. Executing the research project Usable Battery Energy of the material handling equipment was identified to be gradable by 25% to 43% in order to increase equipment availability and thus system efficiency. In the performed case study a system range extension of 19% to 33% was reached by the implementation of a fast engaging charging system using process related idle times. Generally applicable data is required for the design of a scalable simulation to enable the identification of requirements to the design of non-automated material handling system components. The proposed framework forms the basis necessary for the derivation and evaluation of technical and organisational improvement of system efficiency with respect to energy, ecological and economic objectives.

scholarly journals Understanding the Energy Consumption of Battery Electric Buses in Urban Public Transport Systems

2020 ◽  
Vol 12 (23) ◽  
pp. 10007
Author(s):  
Shefang Wang ◽  
Chaoru Lu ◽  
Chenhui Liu ◽  
Yue Zhou ◽  
Jun Bi ◽  
...  
Keyword(s):  
Energy Consumption ◽  
Noise Pollution ◽  
Transport Systems ◽  
Positive Contribution ◽  
Driving Speed ◽  
Urban Public Transport ◽  
Effect Regression ◽  
Battery Energy ◽  
Optimal Driving ◽  
The Relationship

The ever-increasing concerns over urban air quality, noise pollution, and considerable savings in total cost of ownership encouraged more and more cities to introduce battery electric buses (e-bus). Based on the sensor records of 99 e-buses that included over 250,000 h across 4.7 million kilometers, this paper unveiled the relationship between driving behaviors and e-bus battery energy consumption under various environments. Battery efficiency was evaluated by the distance traveled per unit battery energy (1% SoC, State of Charge). Mix effect regression was applied to quantify the magnitude and correlation between multiple factors; and 13 machine learning methods were adopted for enhanced prediction and optimization. Although regenerative braking could make a positive contribution to e-bus battery energy recovery, unstable driving styles with greater speed variation or acceleration would consume more energy, hence reduce the battery efficiency. The timing window is another significant factor and the result showed higher efficiency at night, over weekends, or during cooler seasons. Assuming a normal driving behavior, this paper investigated the most economical driving speed in order to maximize battery efficiency. An average of 19% improvement could be achieved, and the optimal driving speed is time-dependent, ranging from 11 to 18 km/h.

Sign in / Sign up

Export Citation Format

Share Document