Hybrid Energy Storage System interface for Electric Vehicles

Kumar, K.P. Arun Raj; Sreedevi, M.; Mineeshma, G.R.; Chacko, Renji V.; Amal, S

doi:10.1109/pesgre45664.2020.9070367

Cited by 3 publications

(2 citation statements)

References 8 publications

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“…Bidirectional DC/DC can carry out voltage level conversion on a direct current using two modes: boost and buck. In boost mode, energy is absorbed from the battery and released to the DC bus; in buck mode, energy is absorbed from the bus and stored in the battery [14]. The voltage relationship between the respective modes is represented as , Boost 1 , Buck…”

Section: ) Bidirectional Dc/dc Modelmentioning

confidence: 99%

Real-Time Energy Management Strategy of Multi-Wheel Electric Drive Vehicles With Load Power Prediction Function

Chen¹,

Ma²,

Shu-guang³

et al. 2021

IEEE Access

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The lack of a load power prediction function in conventional multi-wheel electric drive vehicles leads to lags in control action. To address this issue, we developed a real-time energy management strategy with improved load power prediction accuracy. Based on an assessment of the overall vehicle structure, a mathematical model for each power source was established using theoretical analysis and data fitting. A method for the joint prediction of non-stationary load power combining Kalman filter and Markov chain forecasting methods was established, and a multi-objective optimization function was constructed under the nonlinear model predictive control framework. To enable real-time optimal control command, a sequential quadratic programming method in the finite time domain was applied. Finally, the multi-power source was optimized and coordinated. Multi-road driving experiments were carried out using a hardware-in-the-loop simulation platform. Comparisons of energy management control strategies with and without power prediction revealed that applying the former enhances the predictability of future load power, significantly optimizes the coordinated control of multiple power sources, improves vehicle fuel economy, and stabilizes bus voltage and battery state of charge. Moreover, it has specific reference significance in engineering application scenarios under conventional model predictive control.INDEX TERMS energy management strategy, integrated power system, load power prediction, model predictive control, multi-wheel electric drive vehicle

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Section: ) Bidirectional Dc/dc Modelmentioning

confidence: 99%

Real-Time Energy Management Strategy of Multi-Wheel Electric Drive Vehicles With Load Power Prediction Function

Chen¹,

Ma²,

Shu-guang³

et al. 2021

IEEE Access

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show abstract

“…Several-port converters like those seen in [16][17][18][19][20][21] are useful for integrating multiple power sources with varying energy capacities to get a controlled output voltage. The issue with that setup is that, in order to avoid power coupling, only one power source is authorized to transmit power into the load at a time.…”

Section: Introductionmentioning

confidence: 99%

Investigation on extendable multiport DC–DC boost converter for hybrid renewable energy systems

Paul¹,

Kumar²,

Carol³

2021

Automatika

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In this work, the integration of renewable hybrid energy (RHE) resources using extendable multiport DC-DC boost converter is investigated. Three renewable energy sources such as solar photovoltaic (PV) system, wind energy system and fuel cell (FC) are integrated into the grid via this converter and grid-tied inverter. The output voltage of the multiport DC-DC boost converter is controlled using adaptive neuro fuzzy inference system-based controller. The overall system model is developed and tested in the MATLAB simulation software and also implemented in real time. The overall system is tested for different operating conditions such as change in irradiance condition of the solar PV panel, change in wind speed condition of the wind turbine, change in hydrogen pressure conditions of the FC and sudden change in load conditions and corresponding results are measured and analysed. The efficiency of the proposed system is about 98.21%. Finally, experimental results of the proposed model are also presented to examine the suitability of the system.

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Electric Propulsion System Powertrain Estimation for Houseboats using Backward Simulation

Sreedevi

Joseph

Ajlif

et al. 2022

2022 IEEE International Conference on Power Electronics, Smart Grid, and Renewable Energy (PESGRE)

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Hybrid Energy Storage System interface for Electric Vehicles

Cited by 3 publications

References 8 publications

Real-Time Energy Management Strategy of Multi-Wheel Electric Drive Vehicles With Load Power Prediction Function

Real-Time Energy Management Strategy of Multi-Wheel Electric Drive Vehicles With Load Power Prediction Function

Investigation on extendable multiport DC–DC boost converter for hybrid renewable energy systems

Electric Propulsion System Powertrain Estimation for Houseboats using Backward Simulation

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