Energy Management of a Multi-Source Vehicle by λ-Control

Castaings, Ali; Lhomme, Walter; Trigui, Rochdi; Bouscayrol, Alain

doi:10.3390/app10186541

Cited by 12 publications

(2 citation statements)

References 42 publications

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“…Although the Unscented Kalman Filter (UKF) algorithm employs statistical linearization to reduce error and calculation, the SOC estimation accuracy still fluctuates along with the unit model [26][27][28][29][30]. Modelbased methods could illustrate the physical and chemical characteristics of the battery, but the correctness of the parameters relies on the accuracy and robustness of the battery model [31][32][33][34][35]. In recent years, battery forecasting has developed towards non-modeling.…”

Section: Introductionmentioning

confidence: 99%

A State of Charge Estimation Approach for Lithium-Ion Batteries Based on the Optimized Metabolic EGM(1,1) Algorithm

Sun

Wang²,

Gao

et al. 2022

Batteries

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The accurate estimation of the state of charge (SOC) for lithium-ion batteries’ performance prediction and durability evaluation is of paramount importance, which is significant to ensure reliability and stability for electric vehicles. The SOC estimation approaches based on big data collection and offline adjustment could result in imprecision for SOC estimation under various driving conditions at different temperatures. In the traditional GM(1,1), the initialization condition and the identifying parameter could not be changed as soon as they are confirmed. Aiming at the requirements of battery SOC estimation with non-linear characteristics of a dynamic battery system, the paper presents a method of battery state estimation based on Metabolic Even GM(1,1) to expand battery state data and introduce temperature factors in the estimation process to make SOC estimation more accurate. The latest information data used in the optimized rolling model is introduced through the data cycle updating. The experimental results show that the optimized MEGM(1,1) effectively considers the influence of initial data, and has higher accuracy than the traditional GM(1,1) model in the application of data expansion. Furthermore, it could effectively solve the problem of incomplete battery information and battery capacity fluctuation, and the dynamic performance is satisfactory to meet the requirements of fast convergence. The SOC estimation based on the presented strategy for power batteries at different temperatures could reach the goal of the overall error within 1% under CLTC conditions with well robustness and accuracy.

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Section: Introductionmentioning

confidence: 99%

A State of Charge Estimation Approach for Lithium-Ion Batteries Based on the Optimized Metabolic EGM(1,1) Algorithm

Sun

Wang²,

Gao

et al. 2022

Batteries

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show abstract

“…In the context of ongoing global warming, with environmental concerns regarding greenhouse gas emissions due to our increasing energy consumption, smart energy management solutions have gained popularity as they have the potential to reduce our impact on the environment and also on our budgets [1]. To face economic and environmental challenges, future ground vehicles must consume less energy and cause less pollution [2].…”

Section: Introductionmentioning

confidence: 99%

Secondary Energy Sources and Their Optimization in the Context of the Tax Gap on Petrol and Diesel

et al. 2021

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This paper presents an energy management strategy for secondary energy sources and their optimization in the context of the tax gap on mineral oils represented by the tax gap on petrol and diesel. Energy companies face drastic economic and environmental challenges; therefore, this area necessarily requires the setting up of transparent economic instruments and, of course, production. The tax gap in VAT collection represents the gap between how much the state could potentially collect from VAT in accordance with the law and how much VAT really comes into the state coffers. The loss of tax revenues is caused by unpaid and undeclared tax liability. The Estimation of the Gap on Corporate Tax in Slovakia is a pilot project of the International Monetary Fund (IMF) in cooperation with the Institute for Financial Policy (IFP). The results present the estimation of the tax gap within a two-year delay. It is necessary to consider the estimation of the tax gap in the last two years as preliminary due to possible revisions of the national accounts data. Estimations of the tax gap from 2010 to 2017 indicate a decreasing trend. The significant part of the tax gap decrease can be observed from 2014. The main factor, which determines this decrease, is the improving condition of the Slovak economy. From the point of view of the tax gap, the volume of losses is decreasing and the volume of profit, from which the tax is paid, is increasing.

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Management of the energy storage hybridization in electric vehicles

Itani¹,

Bernardinis²

2023

Encyclopedia of Electrical and Electronic Power Engineering

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Energy Management of a Multi-Source Vehicle by λ-Control

Cited by 12 publications

References 42 publications

A State of Charge Estimation Approach for Lithium-Ion Batteries Based on the Optimized Metabolic EGM(1,1) Algorithm

A State of Charge Estimation Approach for Lithium-Ion Batteries Based on the Optimized Metabolic EGM(1,1) Algorithm

Secondary Energy Sources and Their Optimization in the Context of the Tax Gap on Petrol and Diesel

Management of the energy storage hybridization in electric vehicles

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