Efficiency Analysis of Various Batteries with Real-time Data on a Hybrid Electric Vehicle

Ekici, Yunus Emre; Dikmen, İsmail Can; NURMUHAMMED, Mustafa; Karadağ, Teoman

doi:10.30939/ijastech..946047

Cited by 8 publications

(3 citation statements)

References 27 publications

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“…MAŞTİ is the first stop and the Inonu University is the last stop. Currently, the operation continues with 22 Trolleybuses on the route [58]. In this study, data obtained from black boxes of Trolleybus vehicles servicing Malatya on the route R0 since 2015 were analyzed [59].…”

Section: Methodsmentioning

confidence: 99%

A Novel Energy Consumption Prediction Model of Electric Buses Using Real-Time Big Data From Route, Environment, and Vehicle Parameters

Ekici,

Akdağ,

Aydin

et al. 2023

IEEE Access

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Electric vehicles (EVs) have positive impacts on reducing oil dependence and exhaust emissions. However, the range problem of EVs is a factor that raises concerns for individual users and bus operators. For this reason, studies on increasing the range of the electric buses in public transportation is extremely important to ensure optimum operation. In this study, a novel energy consumption model, MTECM (Malatya Trolleybus Energy Consumption Model), is developed using the multi-parameter linear regression method. The real-time big data was collected on the field of Trolleybus vehicles, which have been operated for 8 years in Malatya / Turkey. Firstly, by calculating the correlation of the parameters affecting this model, the parameters that are suitable for the purpose of our study are determined and regression analysis is performed on the original Trolleybus dataset. A total of 75.497.472 data are analyzed for this model. The RMSE (Root Mean Square Error) of MTECM is calculated as 0.29996. The trained model is applied to the 10 busiest routes in Malatya in terms of passenger density. The RMSE value on these routes is calculated between 0.30299 and 0.31421. Based on the results, with lower error rates, the proposed novel model is more efficient than other studies in the literature. In addition, energy consumption can be calculated for any route planned to establish an electric bus operation with MTECM. Therefore, according to the consumption obtained, the correct determination and selection of parameters that significantly affect the investment cost such as route, vehicle length, engine power, and battery capacity can be made.INDEX TERMS Big data analysis, electric vehicle, electric bus, machine learning, regression, trolleybus.

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Section: Methodsmentioning

confidence: 99%

A Novel Energy Consumption Prediction Model of Electric Buses Using Real-Time Big Data From Route, Environment, and Vehicle Parameters

Ekici,

Akdağ,

Aydin

et al. 2023

IEEE Access

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“…Lithium-ion batteries are a serious alternative to the Ni-MH batteries used in most HEVs [51]. One of the battery types frequently used in EVs is Ni-MH batteries [52]. Additionally, as of 2017, 85% of the batteries used in the listed HEVs were based on Ni-MH batteries [53].…”

Section: Pbo2 + H2s04→ Pbso4+ H2o + ½O2mentioning

confidence: 99%

Review of Mechanical, Electrochemical, Electrical, and Hybrid Energy Storage Systems Used for Electric Vehicles

Kurtulmuş,

Karakaya

2024

International Journal of Automotive Science and Technology

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The population rate in the world is increasing rapidly. Depending on the population, the need for transportation increases at the same rate. Traditional vehicles, which provide great convenience in transportation, bring with them some disadvantages. For example, the fossil fuel used in conventional vehicles creates greenhouse gases such as CO2 and N2O. This has a negative impact on global warming. To eliminate these negativities, interest in electric vehicle (EV) and hybrid electric vehicles (HEV) technology studies has increased recently. Some problems have arisen with these technological studies. The range problem in vehicles is the biggest of these problems. Therefore, various solutions are sought for energy storage problems in vehicles. In this article, studies on HEV and energy storage in EVs are examined. According to the data obtained because of this examination, the performance analysis of the Energy Storage Systems (ESS) was made. The performances of the electrochemical batteries used in HEVs and EVs were compared. In addition to these, flywheel energy storage system was also investigated in HEVs and EVs to recover the energy lost because of braking.

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“…Due to its many advantages, almost all PHEV models use lithium battery chemistry. There are studies that have researched various battery chemistries for EVs especially lithium batteries [3][4][5][6]. One study compares the final state of charge of a battery pack with various battery types and lithium-based batteries lead four other chemistries studied [4].…”

Section: Introductionmentioning

confidence: 99%

Cost/Performance Analysis of Battery Pack placed in Spare Tire Area for Extending the Range of Hybrid, and Electric Vehicles

Nurmuhammed,

Karadağ

2024

International Journal of Automotive Science and Technology

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Recently, electric vehicles have been an alternative form of transportation promising a bright future as sales figures are increasing rapidly beyond expectations. In the near fu-ture, electric vehicles are expected to dominate the market with numerous advantages over vehicles with internal combustion engines. The hybrid electric vehicles are often con-sidered a transition between the two due to added advantages of both models. Out of hy-brid models, plugin hybrid vehicles have more resemblance to the fully electric vehicles because of longer electric range and lower cost per mile. This paper investigates the use of the spare tire location to convert an existing battery pack or to install a new battery pack for a hybrid vehicle. Cost and range calculations are performed based on two most com-monly sold vehicles that use 16”, 17” and 18” size tires. Resulting battery packs are demonstrated through various battery dimensions and chemistries. Results are provided with cost and environmental benefits of utilizing an electric power for driving.

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Efficiency Analysis of Various Batteries with Real-time Data on a Hybrid Electric Vehicle

Cited by 8 publications

References 27 publications

A Novel Energy Consumption Prediction Model of Electric Buses Using Real-Time Big Data From Route, Environment, and Vehicle Parameters

A Novel Energy Consumption Prediction Model of Electric Buses Using Real-Time Big Data From Route, Environment, and Vehicle Parameters

Review of Mechanical, Electrochemical, Electrical, and Hybrid Energy Storage Systems Used for Electric Vehicles

Cost/Performance Analysis of Battery Pack placed in Spare Tire Area for Extending the Range of Hybrid, and Electric Vehicles

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