Ambient temperature and relative humidity-based drift correction in frequency domain electromagnetics using machine learning

Electromagnetic instrument responses suffer from signal drift that results in a variable response at a given location over time. If left uncorrected, spatiotemporal aliasing can manifest and global trends or abrupt changes might be observed in the data, which are independent of subsurface electromagnetic variations. By performing static ground measurements, we characterized drift patterns of different electromagnetic instruments. Next, we performed static measurements at an elevated height, approximately 4 metre above ground level, to collect a data set that forms the basis of a new absolute calibration methodology. By additionally logging ambient temperature variations, battery voltage and relative humidity, a relation between signal drift and these parameters was modelled using a machine learning (ML) approach. The results show that it was possible to mitigate the effects of signal drift; however, it was not possible to completely eliminate them. The reason is three-fold: (1) the ML algorithm is not yet sufficiently adapted for accurate prediction; (2) signal instability is not explained sufficiently by ambient temperature, relative humidity and battery voltage; and (3) the black-box internal (factory) calibration impeded direct access to raw data,which prevents accurate evaluation of the proposed methodology. However, the results suggest that these challenges are not insurmountable and thatML can form a viable approach in tackling the drift problem instrument specific in the near future.

A Battery Voltage Level Monitoring System for Telecommunication Towers

Voltage fluctuations in batteries form a major challenge the telecommunication towers face. These fluctuations mostly occur due to poor management and the lack of a battery voltage level monitoring system. The current paper presents a battery voltage-level monitoring system to be used in telecommunication towers. The proposed solution is incorporated with a centralized mobile application dashboard for accessing the live data of the installed battery, integrated with voltage-level, current, temperature, fire, and gas sensors. An Arduino Uno microcontroller board is used to process and analyze the collected data from the sensors. The Global Service Message (GSM) module is used to monitor and store data to the cloud. Users are alerted in the case of low voltage, fire, and increase in harmful gases in the tower through Short Message Service (SMS). The experiment was conducted at Ngorongoro and Manyara telecommunication towers. The developed system can be used in accessing battery information remotely while allowing real-time continuous monitoring of battery usage. The proposed battery voltage-level monitoring system contributes to the elimination of battery hazards in towers. Therefore, the proposed battery voltage level monitoring system can be adopted by telecommunication tower engineers for the reduction of voltage fluctuation risks.

Designing and performance investigation of permanent magnet motor prototype for UTV electric drive train application

<span lang="EN-US">The dynamic design specifications of a vehicle are used to define the required torque and speed of a permanent magnet motor. This is due to providing clear instructions on the intent, performance, and construction of a vehicle. Therefore, this study aims to determine an engineering design and prototyping process of a Permanent Magnet Motor, to be used as an electric powertrain in a Utility Vehicle. Based on being used in severe road condition (steep inclination and off road), the vehicle should be able to handle a 45° inclination with total payload of approximately 250 kg. Using a rear-wheel-drive traction, its weight should also be less than 1000 kg. Furthermore, the motor should be operated at a maximum battery voltage of 100 V. According to the requirements, the electric powertrain should further have the ability to deliver a torque of approximately 1600 Nm on both rear wheels. Using a finite element method to simulate performances, transmission was coupled to the motor in providing the required torque. In addition, the motor prototype was subsequently manufactured and tested using a dynamometer. The results showed that the motor produced 19.6 kW, 5600 RPM, and 75 Nm at 96 V. Therefore, the design and prototyping process of the motor satisfied all the required specification.</span>

Electrical Interoperability Evaluating of Wireless Electric Vehicle Charging Systems Based on Impedance Space

In the commercialization process of wireless electric vehicle charging (WEVC), it is essential to ensure the interoperability between diverse WEVC systems due to the wide application of various coil configurations and compensation topologies. This paper proposes a novel electrical interoperability evaluation method based on impedance indices and corresponding feasible space in the complex plane. Firstly, the electromagnetic description of the coil system is introduced to reveal the energy flow process of WEVC system. Further, two key impedance indices and their feasible space are derived and verified. Interoperability evaluation results show that the reference devices in Chinese WEVC standard GB/T 38775.6 and GB/T 38775.7 are able to achieve the requirements of power capability. Moreover, it is necessary to reduce the duty cycle of rectifier when the battery voltage rises so as to narrow down the variation of load resistance and avoid dangerous working conditions. The proposed method can effectively evaluate the electrical interoperability of WEVC systems from different manufacturers under different power or distance levels before conducting experiments.

Fuzzy Classification Based Driving Distance Estimation for Electric Vehicles

Electric vehicle technology is an essential research field for improving full-electric vehicle (FEVs) capabilities. Different subsystem parameters in the FEVs should be monitored on a regular basis. The better these subsystems are used, the better the FEVs' performance, life, and range become. Nowadays, estimation of the state of charge (SoC) of the batteries and the driving distance is the area not been standardized sufficiently. In this study, a novel fuzzy classification method (FCM) is proposed to make the exact driving distance estimation of FEVs. The proposed FCM considers the consumed power and parameters of the battery under dynamic conditions. A test location was selected for the proposed FCM and tested under 3 different test conditions, namely, no-load, half-load and full-load conditions. Also, the performance of FCM is studied under several slope conditions, and the result shows that if the battery voltage decreases then the power consumed by the vehicle is improved in the uphill travel and the battery voltage is normal and the power consumption of the vehicle is decreased in the downhill drive. Finally, the drive distance of the proposed FCM is determined. HIGHLIGHTS Fuzzy classification based driving distance estimation for full-electric vehicle is proposed Parameters of battery and power consumption has been considered under dynamic condition CAN communication is established between different subsystems of electric vehicle Three test conditions (no-load, half load, and full load) have been considered

Demonstration of a Novel Alternating Current Hybrid Concept for a Fuel Cell–Battery Hybrid Electric Aircraft

Hybrid electric aircraft offer the potential to decrease emissions from air travel. A new hybrid concept is proposed for a fuel cell-battery hybrid aircraft. In contrast to existing hybrids, the proposed concept puts a battery directly on the AC phases of the motor, which together with a suitable switching circuit superimposes the DC voltage from the battery on the AC voltage of the motor phase providing a voltage boost depending on the battery voltage, which can be used during a high-power demand flight phase. The system is also capable of recharging the battery during flight. The necessary switching architecture was developed and modeled in MATLAB/Simulink to verify the concept and an experimental setup was built for demonstrating the functionality. Simulation and experimental results showed a very good agreement which is very promising for the proposed new hybrid topology.

Analysis of ocean wave power plant buoy system at Kelong

The potential of sea waves, located precisely in the Berakit area, can be used as electrical energy on a small scale. Kelong is a floating house situated on the coast, which anglers (fishermen) use to catch fish. In the Bintan area, there are two types of kelong, namely floating kelong and cacak (permanent) kelong. Floating kelong, as the name implies, is a kelong that can be moved anywhere. During the fish season, the kelong are offered to the middle of the sea, but if the west wind season or not during the fish season, the kelong will be brought ashore. On the other hand, kelong cacak are usually not far from the beach or coast and cannot be moved and operated at night by using a lamp to catch cuttlefish or anchovies. This research was conducted on Kelong Cacak and Floating Kelong (pontoon) located in Berakit, Disability Telok Sebong, Kabubapen Bintan. The power generation system was built using the buoy method. Based on the research results, the wave power plant can be driven by sea waves with an average height of 6 cm and produces a voltage and continuously the voltage is not always stable. The maximum peak output voltage is up to 15 Volt DC; after knowing the test results, the power plant can supply as a charger for the battery in the kelong cacak of 0.8839 Volt DC with an average battery voltage of 10.052 Volt DC and total voltage charging is 0.37 Volt DC, with average battery voltage 11.4902 Volt DC on Floating Kelong (Pontoon).

Research on Modeling and Power Algorithm of Photovoltaic Cells for Solar Cars

Solar photovoltaic cells will be an effective supplement to electric vehicle batteries. In order to make the photovoltaic system of the solar car provide reliable power, this paper models the photovoltaic cell and designs the maximum power point (MPP) tracking algorithm based on three-point sampling with a fixed voltage. In addition, considering that the output power will change when the voltage and radiation intensity change under the peak power of the solar vehicle, the prediction of the peak output power of the photovoltaic array considering the influence of the radiation intensity and battery voltage is put forward for the first time. Experiments show that the designed power algorithm runs stably, and the power generation power prediction error is less than 1%. The peak output power prediction of the photovoltaic array takes into account the effects of real-time radiation intensity and battery voltage fluctuations, making the peak power prediction of the vehicle more accurate.