scholarly journals Development of an Android OS Based Controller of a Double Motor Propulsion System for Connected Electric Vehicles and Communication Delays Analysis

2015 ◽  
Vol 2015 ◽  
pp. 1-12
Author(s):  
Pedro Daniel Urbina Coronado ◽  
Horacio Ahuett-Garza ◽  
Vishnu-Baba Sundaresan ◽  
Ruben Morales-Menendez

Developments of technologies that facilitate vehicle connectivity represent a market demand. In particular,mobile device(MD) technology provides advanced user interface, customization, and upgradability characteristics that can facilitate connectivity and possibly aid in the goal of autonomous driving. This work explores the use of a MD in the control system of a conceptualelectric vehicle(EV). While the use of MD for real-time control and monitoring has been reported, proper consideration has not been given to delays in data flow and their effects on system performance. The motor of a novel propulsion system for an EV was conditioned to be controlled in a wireless local area network by an ecosystem that includes a MD and an electronic board. An intended accelerator signal is predefined and sent to the motor and rotational speed values produced in the motor are sent back to the MD. Sample periods in which the communication really occurs are registered. Delays in the sample periods and produced errors in the accelerator and rotational speed signals are presented and analyzed. Maximum delays found in communications were of 0.2 s, while the maximum error produced in the accelerator signal was of 3.54%. Delays are also simulated, with a response that is similar to the behavior observed in the experiments.

Author(s):  
K. M. K. Daray ◽  
P. A. G. Todoc ◽  
C. J. S. Sarmiento

Abstract. The indoor positioning problem is not the unavailability of indoor positioning technology, but the difficulty of arriving at an acceptable compromise of technical constraints like cost, performance, ease of use, and availability of technologies. In a developing country such as the Philippines, these constraints have more weight and can restrict the advancement of indoor positioning.This study investigates the use of Bluetooth Low Energy (BLE) and Wireless Local Area Network (WLAN) in Euclidean distance computation, which implies prospect use for indoor positioning through trilateration. It is a proof-of-concept study that BLE and WLAN, using readily-available services such as Nearby Application Programming Interface (API) and beacon simulators, can be used for indoor positioning. This method offers a better trade-off between cost, power, and accuracy.Nearby API and a regular beacon simulator application were used as beacons. The received signal strength interface (RSSI) was measured and used to calculate the Euclidean distance. From each beacon were calculated four different distances, Nearby yielding a maximum error of 26% and a minimum of 4%. The beacon simulator was less accurate and had a maximum error of 60.5% and a minimum of 4%. This shows that it is possible to calculate Euclidean distance using WLAN and BLE, and that Nearby API, which uses both, was more accurate than the beacon simulator, which used only BLE.


Author(s):  
Chaithra. H. U ◽  
Vani H.R

Now a days in Wireless Local Area Networks (WLANs) used in different fields because its well-suited simulator and higher flexibility. The concept of WLAN  with  advanced 5th Generation technologies, related to a Internet-of-Thing (IOT). In this project, representing the Network Simulator (NS-2) used linked-level simulators for Wireless Local Area Networks and still utilized IEEE 802.11g/n/ac with advanced IEEE 802.11ah/af technology. Realization of the whole Wireless Local Area Networking linked-level simulators inspired by the recognized Vienna Long Term Evolution- simulators. As a outcome, this is achieved to link together that simulator to detailed performances of Wireless Local Area Networking with Long Term Evolution, operated in the similar RF bands. From the advanced 5th Generation support cellular networking, such explore is main because different coexistences scenario can arise linking wireless communicating system to the ISM and UHF bands.


Jurnal Teknik ◽  
2018 ◽  
Vol 7 (1) ◽  
Author(s):  
Heru Abrianto

Microstrip antenna which designed with dual feeding at 2.4 GHz and 5.8 GHz can meet WLAN (Wireless Local Area Network) application.Antenna fabrication use PCB FR4 double layer with thickness 1.6 mm and dielectric constant value 4.4. The length of patch antenna according to calculation 28.63 mm, but to get needed parameter length of patch should be optimized to 53 mm. After examination, this antenna has VSWR 1.212 at 2.42 GHz and 1.502 at 5.8 GHz, RL -13.94 dB at 2.42 GHz and -20.357 dB at 5.8 GHz, gain of antenna 6.16 dB at 2.42 GHz and 6.91 dB at 5.8 GHz, the radiation pattern is bidirectional. Keywords : microstrip antenna, wireless LAN, dual polarization, single feeding technique


2018 ◽  
Author(s):  
Kiramat

IEEE 802.11 is a set of media access control (MAC) and physical layer (PHY) specifications for implementing wireless local area network (WLAN) computer communications. Maintained by the Institute of Electrical and Electronics Engineers (IEEE) LAN/MAN Standards Committee (IEEE 802). This document highlights the main features of IEEE 802.11n variant such as MIMO, frame aggregation and beamforming along with the problems in this variant and their solutions


2020 ◽  
Vol 1550 ◽  
pp. 032078
Author(s):  
Kaigang Fan ◽  
Xin Chen ◽  
Biao Zhao ◽  
Jiale Wang ◽  
Wenbin Cui ◽  
...  

Sensors ◽  
2021 ◽  
Vol 21 (6) ◽  
pp. 2000
Author(s):  
Marius Laska ◽  
Jörg Blankenbach

Location-based services (LBS) have gained increasing importance in our everyday lives and serve as the foundation for many smartphone applications. Whereas Global Navigation Satellite Systems (GNSS) enable reliable position estimation outdoors, there does not exist any comparable gold standard for indoor localization yet. Wireless local area network (WLAN) fingerprinting is still a promising and widely adopted approach to indoor localization, since it does not rely on preinstalled hardware but uses the existing WLAN infrastructure typically present in buildings. The accuracy of the method is, however, limited due to unstable fingerprints, etc. Deep learning has recently gained attention in the field of indoor localization and is also utilized to increase the performance of fingerprinting-based approaches. Current solutions can be grouped into models that either estimate the exact position of the user (regression) or classify the area (pre-segmented floor plan) or a reference location. We propose a model, DeepLocBox (DLB), that offers reliable area localization in multi-building/multi-floor environments without the prerequisite of a pre-segmented floor plan. Instead, the model predicts a bounding box that contains the user’s position while minimizing the required prediction space (size of the box). We compare the performance of DLB with the standard approach of neural network-based position estimation and demonstrate that DLB achieves a gain in success probability by 9.48% on a self-collected dataset at RWTH Aachen University, Germany; by 5.48% for a dataset provided by Tampere University of Technology (TUT), Finland; and by 3.71% for the UJIIndoorLoc dataset collected at Jaume I University (UJI) campus, Spain.


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