The Concept of Using an Expert System and Multi-Valued Logic Trees to Assess the Energy Consumption of an Electric Car in Selected Driving Cycles

Deptuła, Adam; Augustynowicz, A.; Stosiak, Michał; Towarnicki, Krzysztof; Karpenko, Mykola

doi:10.3390/en15134631

Cited by 7 publications

(7 citation statements)

References 62 publications

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“…The BP neural network is a multi-layer feed-forward neural network [28][29][30]. The neurons of the proposed algorithm can be divided into three layers: input layer, hidden layer, and output layer.…”

Section: Bp Neural Networkmentioning

confidence: 99%

Design and Evaluation of Wheat Moisture Content Detection Device Based on a Stripline

Song,

Zhang,

et al. 2024

Agriculture

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The detection of the moisture content of wheat is an important index used to measure the quality and preservation of wheat. In order to rapidly and non-destructively detect the moisture content of wheat, in this study, we designed a stripline detection device that measures 151 frequency points in the 50–200 MHz frequency range with a vector network analyzer. Random forest (RF), extreme learning machine (ELM), and BP neural network prediction models were established, using the frequency, temperature, volume density and dielectric constant as input and the water content as output. It was shown that, in the frequency range 50–200 MHz, the permittivity of wheat decreases as the frequency increases, and that this is negatively correlated. The dielectric constant of wheat increases as the moisture content, temperature, and bulk density increase, and these are positively correlated. The random forest (RF) prediction model, which uses the frequency, temperature, effective dielectric constant εeff. and volume density as inputs and the wheat moisture content as the output, demonstrates the best performance. The determination coefficient (R2) = 0.99977, the mean absolute error (MAE) = 0.044368, the mean square error (MAE) = 0.0053011, and the root mean square error (RMSE) = 0.072809. This study provides a new device and method for the detection of the moisture content of wheat. The device is small and is not easily disturbed by the external environment. It can be measured in a variety of conditions and is important for the development of low-cost, high-precision, and portable devices for the detection of the moisture content of wheat.

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Section: Bp Neural Networkmentioning

confidence: 99%

Design and Evaluation of Wheat Moisture Content Detection Device Based on a Stripline

Song,

Zhang,

et al. 2024

Agriculture

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“…Storing energy seems to be necessary. The battery is the most commonly used storage system in a standalone system [29]. Lithium-ion batteries are chosen as a suitable storage system for electric vehicles due to their power density, high specific energy, and long life expectancy.…”

Section: Modeling Of the Lithium-ion Batterymentioning

confidence: 99%

“…Another interesting research field in electric vehicles concerns vehicle autonomy [29,30]. Suggested solutions for improving electric vehicle autonomy can be divided into two kinds.…”

Section: Introductionmentioning

confidence: 99%

Robust Optimization and Power Management of a Triple Junction Photovoltaic Electric Vehicle with Battery Storage

Hamed

Sbita

et al. 2022

Sensors

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This paper highlights a robust optimization and power management algorithm that supervises the energy transfer flow to meet the photovoltaic (PV) electric vehicle demand, even when the traction system is in motion. The power stage of the studied system consists of a triple-junction PV generator as the main energy source, a lithium-ion battery as an auxiliary energy source, and an electric vehicle. The input–output signal adaptation is made by using a stage of energy conversion. A bidirectional DC-DC buck-boost connects the battery to the DC-link. Two unidirectional boost converters interface between the PV generator and the DC link. One is controlled with a maximum power point tracking (MPPT) algorithm to reach the maximum power points. The other is used to control the voltage across the DC-link. The converters are connected to the electric vehicle via a three-phase inverter via the same DC-link. By considering the nonlinear behavior of these elements, dynamic models are developed. A robust nonlinear MPPT algorithm has been developed owing to the nonlinear dynamics of the PV generator, metrological condition variations, and load changes. The high performance of the MPPT algorithm is effectively highlighted over a comparative study with two classical P & O and the fuzzy logic MPPT algorithms. A nonlinear control based on the Lyapunov function has been developed to simultaneously regulate the DC-link voltage and control battery charging and discharging operations. An energy management rule-based strategy is presented to effectively supervise the power flow. The conceived system, energy management, and control algorithms are implemented and verified in the Matlab/Simulink environment. Obtained results are presented and discussed under different operating conditions.

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“…Sistem pakar (expert system) adalah cabang dari kecerdasan buatan (artificial intelligence) yang menciptakan ekstensi untuk mengkhususkan pengetahuan memecahkan masalah melalui pengetahuan seorang pakar. Pengetahuan dalam expert system berasal dari manusia yang didapat melalui pendidikan serta pengetahuan yang berasal dari buku referensi orang lain, jurnal, atau karya ilmiah untuk DOI: 10.35508/jicon.v10i2.8187 ISSN: 2337-7631 (printed) ISSN: 2654-4091 (online) mentransfer pengetahuan ke komputer sehingga dapat menyelesaikan masalah seperti yang dilakukan komputer pada umumnya [1].…”

Section: Pendahuluanunclassified

Expert System Diagnosis of Kidney Disease Using Forward Chaining

Yadi¹

2022

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Kidney disease is a disease that is often experienced by people aged over 50 years. Several factors that cause kidney disease include hypertension, diabetes, obesity, smoking and family history of kidney disease sufferers. As many as 42,000 people per year die from kidney disease. Sufferers in Indonesia, which is estimated by the Ministry of Health, based on the 2013-2018 Basic Health Research (Riset Kesehatan Dasar (RIKESDA)) the number of patients experiencing kidney disease symptoms continues to grow to reach 739,208 people in 2013 while chronic kidney sufferers. It was recorded that in 2020 BPJS Kesehatan spent a large enough budget for kidney failure patients as many as 1,763,260 patients. The high number of patients with kidney disease was due to a lack of physical activity and consumption of healthy foods and fruits and vegetables. Therefore, it is necessary to detect as early as possible to prevent the onset of kidney disease. Technology is one of the disseminations of good information in handling kidney disease. This study aims to build an expert system for diagnosing kidney disease. The results of the research on an expert system for diagnosing kidney disease based on a website that can be accessed by the public by providing information on the detection of kidney disease symptoms with 27 symptoms. The process of tracking symptoms using forward chaining. Conclusion tests carried out using black box and usability testing have been running well, as seen from the input and output functionality on the system used by the user. In addition, the expert system helps in providing information to the public to detect the symptoms of kidney disease as early as possible.

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The Concept of Using an Expert System and Multi-Valued Logic Trees to Assess the Energy Consumption of an Electric Car in Selected Driving Cycles

Cited by 7 publications

References 62 publications

Design and Evaluation of Wheat Moisture Content Detection Device Based on a Stripline

Design and Evaluation of Wheat Moisture Content Detection Device Based on a Stripline

Robust Optimization and Power Management of a Triple Junction Photovoltaic Electric Vehicle with Battery Storage

Expert System Diagnosis of Kidney Disease Using Forward Chaining

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