Simulation of Battery Life Time Evaluation for Automobiles

2006 ◽  
Author(s):  
K. Kobayashi ◽  
R. Nishimura ◽  
G. Fujita ◽  
T. Fukada
Keyword(s):  
Life Time ◽  
Battery Life ◽  
Time Evaluation

Energy Efficient Image Compression and Transmission in WSN

2016 ◽  
pp. 67-78
Author(s):  
Wajeeha Aslam ◽  
Muazzam A. Khan ◽  
M. Usman Akram ◽  
Nazar Abbas Saqib ◽  
Seungmin Rho
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Image Compression ◽  
Sensor Network ◽  
Image Data ◽  
Life Time ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Battery Life

Wireless sensor networks are greatly habituated in widespread applications but still yet step behind human intelligence and vision. The main reason is constraints of processing, energy consumptions and communication of image data over the sensor nodes. Wireless sensor network is a cooperative network of nodes called motes. Image compression and transmission over a wide ranged sensor network is an emerging challenge with respect to battery, life time constraints. It reduces communication latency and makes sensor network efficient with respect to energy consumption. In this paper we will have an analysis and comparative look on different image compression techniques in order to reduce computational load, memory requirements and enhance coding speed and image quality. Along with compression, different transmission methods will be discussed and analyzed with respect to energy consumption for better performance in wireless sensor networks.

Cost-Effective Energy Management for Hybrid Electric Heavy-Duty Truck Including Battery Aging

2013 ◽  
Author(s):  
T. H. Pham ◽  
P. P. J. van den Bosch ◽  
J. T. B. A. Kessels ◽  
R. G. M. Huisman
Keyword(s):  
Energy Management ◽  
Combustion Engine ◽  
Life Time ◽  
Battery Life ◽  
Heavy Duty ◽  
Energy Management Strategy ◽  
Battery Power ◽  
Battery Capacity ◽  
Hybrid Electric ◽  
Power Capability

Battery temperature has large impact on battery power capability and battery life time. In Hybrid Electric Heavy-duty trucks (HEVs), the high-voltage battery is normally equipped with an active Battery Thermal Management System (BTMS) guaranteeing a desired battery life time. Since the BTMS can consume a substantial amount of energy, this paper aims at integrating the Energy Management Strategy (EMS) and BTMS to minimize the overall operational cost of the truck (considering diesel fuel cost and battery life time cost). The proposed on-line strategy makes use of the Equivalent Consumption Minimization Strategy (ECMS) along with a physics-based approach to optimize both the power split (between the Internal Combustion Engine (ICE) and the Motor Generator (MG)) and the BTMS’s operation. The strategy also utilizes a quasi-static battery cycle-life model taking into account the effects of battery power and battery temperature on the battery capacity loss. Simulation results present an appropriate strategy for EMS and BTMS integration, and demonstrate the trade-off between the total vehicle fuel consumption and the battery life time.

scholarly journals Energy Consumption Improvement of OOK Transmitter Based on Minimum Energy Coding

2021 ◽  
Author(s):  
yue peng ◽  
Guillaume Andrieux ◽  
Jean-francois diouris
Keyword(s):  
Energy Consumption ◽  
Minimum Energy ◽  
Closed Form Solution ◽  
Life Time ◽  
Form Solution ◽  
Battery Life ◽  
Transmission Range ◽  
Energy Consumption Model ◽  
Time Requirements ◽  
Consumption Model

Abstract Energy consumption of Wireless Sensor Networks (WSNs) including OOK transmitter is important for short range transmission and long battery life time requirements. In this paper, the Minimum Energy (ME) coding strategy is adopted to improve the energy efficiency of an OOK transmitter. We first give the energy consumption model based on a real OOK transmitter, which can completely switch off the transmitter during the transmission of low bit '0' and has an energy effciency of 52 pJ/bit. Based on this energy consumption model, ME-Coding provides an energy effciency of 30 pJ/bit for coding size k = 3. Moreover, larger coding size others more significant improvement, at the sacrifice of spectral effciency and transmission range. In this paper, we have also determined a closed-form solution for the optimal coding size for a given transmission range constraint.

Design of Hybridized Wireless Sensor Network using K-Means Clustering and Genetic Algorithm

2017 ◽  
Vol 2 (5) ◽  
pp. 1-6
Author(s):  
M. D. Gbolagade ◽  
R. G. Jimoh ◽  
K. A. Gbolagade ◽  
O. V. Mejabi
Keyword(s):  
Data Transfer ◽  
Cluster Head ◽  
Simulated Data ◽  
Life Time ◽  
Base Station ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Battery Life ◽  
Cluster Heads ◽  
Main Challenge

Prolonging the network lifetime in wireless sensor networks (WSNs), Clustering has been recognized has one of the significant methods in achieving this, It entails grouping of sensor nodes into clusters and electing cluster heads (CHs) for all the clusters. CH’s accept data from relevant cluster’s nodes and forward the aggregate data to base station. A main challenge in WSNs is the selection of appropriate cluster heads. This work proposes a system that is efficient, scalable and load balanced. The proposed scheme combines two known algorithms namely k-means clustering and genetic algorithms based on the weaknesses identified in the two. The simulated data is obtained through the enhancement of clustering by the cluster head (base station) that helps in locating the nearest node that is important in the data transfer instead of transferring to a node that is not necessary, thereby wasting time and resources. The obtained simulation results indicate that this approach is efficient and last longer in elongating the battery life time than the conventional method by 60%.

scholarly journals Energy-Aware Management in Multi-UAV Deployments: Modelling and Strategies

Sensors ◽  
2020 ◽  
Vol 20 (10) ◽  
pp. 2791
Author(s):  
Victor Sanchez-Aguero ◽  
Francisco Valera ◽  
Ivan Vidal ◽  
Christian Tipantuña ◽  
Xavier Hesselbach
Keyword(s):  
Heuristic Algorithm ◽  
Optimal Solution ◽  
Exact Result ◽  
Life Time ◽  
Ground Truth ◽  
Battery Life ◽  
Energy Aware ◽  
Mission Duration ◽  
Replacement Procedure ◽  
Multi Uav

Nowadays, Unmanned Aerial Vehicles (UAV) are frequently present in the civilian environment. However, proper implementations of different solutions based on these aircraft still face important challenges. This article deals with multi-UAV systems, forming aerial networks, mainly employed to provide Internet connectivity and different network services to ground users. However, the mission duration (hours) is longer than the limited UAVs’ battery life-time (minutes). This paper introduces the UAV replacement procedure as a way to guarantee ground users’ connectivity over time. This article also formulates the practical UAV replacements problem in moderately large multi-UAV swarms and proves it to be an NP-hard problem in which an optimal solution has exponential complexity. In this regard, the main objective of this article is to evaluate the suitability of heuristic approaches for different scenarios. This paper proposes betweenness centrality heuristic algorithm (BETA), a graph theory-based heuristic algorithm. BETA not only generates solutions close to the optimal (even with 99% similarity to the exact result) but also improves two ground-truth solutions, especially in low-resource scenarios.

scholarly journals A System for Monitoring Breathing Activity Using an Ultrasonic Radar Detection with Low Power Consumption

2019 ◽  
Vol 8 (2) ◽  
pp. 32 ◽  
Author(s):  
Ali Al-Naji ◽  
Ali J. Al-Askery ◽  
Sadik Kamel Gharghan ◽  
Javaan Chahl
Keyword(s):  
Power Consumption ◽  
Low Power ◽  
Monitoring System ◽  
Life Time ◽  
Mobile Telephone ◽  
Physical Contact ◽  
Low Power Consumption ◽  
Battery Life ◽  
Radar Detection ◽  
Abnormal Breathing

Continuous monitoring of breathing activity plays a major role in detecting and classifying a breathing abnormality. This work aims to facilitate detection of abnormal breathing syndromes, including tachypnea, bradypnea, central apnea, and irregular breathing by tracking of thorax movement resulting from respiratory rhythms based on ultrasonic radar detection. This paper proposes a non-contact, non-invasive, low cost, low power consumption, portable, and precise system for simultaneous monitoring of normal and abnormal breathing activity in real-time using an ultrasonic PING sensor and microcontroller PIC18F452. Moreover, the obtained abnormal breathing syndrome is reported to the concerned physician’s mobile telephone through a global system for mobile communication (GSM) modem to handle the case depending on the patient’s emergency condition. In addition, the power consumption of the proposed monitoring system is reduced via a duty cycle using an energy-efficient sleep/wake scheme. Experiments were conducted on 12 participants without any physical contact at different distances of 0.5, 1, 2, and 3 m and the breathing rates measured with the proposed system were then compared with those measured by a piezo respiratory belt transducer. The experimental results illustrate the feasibility of the proposed system to extract breathing rate and detect the related abnormal breathing syndromes with a high degree of agreement, strong correlation coefficient, and low error ratio. The results also showed that the total current consumption of the proposed monitoring system based on the sleep/wake scheme was 6.936 mA compared to 321.75 mA when the traditional operation was used instead. Consequently, this led to a 97.8% of power savings and extended the battery life time from 8 h to approximately 370 h. The proposed monitoring system could be used in both clinical and home settings.

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