Online Parameter Identification for State of Power Prediction of Lithium-ion Batteries in Electric Vehicles Using Extremum Seeking

There are different types of rechargeable batteries, but lithium-ion battery has proven to be superior due to its features including small size, more volumetric energy density, longer life, and low maintenance. However, lithium-ion batteries face safety issues as one of the common challenges in their development, necessitating research in this area. For the safe operation of lithium-ion batteries, state estimation is very significant and battery parameter identification is the core in battery state estimation. The battery management system for electric vehicle application must perform a few estimation tasks in real-time. Battery state estimation is defined by the battery model adopted and its accuracy impacts the accuracy of state estimation. The knowledge of the actual operating conditions of electric vehicles requires the application of an accurate battery model; for our research, we adopted the use of the dual extended Kalman filter and it demonstrated that it yields more accurate and robust state estimation results. Since no single battery model can satisfy all the requirements of battery estimation and parameter identification, the hybridization of battery models together with the introduction of internal sensors to batteries to measure battery internal reactions is very essential. Similarly, since the current battery models rarely consider the coupling effect of vibration and temperature dynamics on model parameters during state estimation, this research goal is to identify the battery parameters and then present the effect of the vibration and temperature dynamics in battery state estimation.

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A Review of Equivalent Circuit Model Based Online State of Power Estimation for Lithium-Ion Batteries in Electric Vehicles

Vehicles ◽

10.3390/vehicles4010001 ◽

2021 ◽

Vol 4 (1) ◽

pp. 1-31

Author(s):

Ruohan Guo ◽

Weixiang Shen

Keyword(s):

Lithium Ion Batteries ◽

Equivalent Circuit ◽

Electric Vehicles ◽

Power Flow ◽

Equivalent Circuit Model ◽

Lithium Ion ◽

Circuit Model ◽

Estimation Methods ◽

State Of Power ◽

Transportation Electrification

With rapid transportation electrification worldwide, lithium-ion batteries have gained much attention for energy storage in electric vehicles (EVs). State of power (SOP) is one of the key states of lithium-ion batteries for EVs to optimise power flow, thereby requiring accurate online estimation. Equivalent circuit model (ECM)-based methods are considered as the mainstream technique for online SOP estimation. They primarily vary in their basic principle, technical contribution, and validation approach, which have not been systematically reviewed. This paper provides an overview of the improvements on ECM-based online SOP estimation methods in the past decade. Firstly, online SOP estimation methods are briefed, in terms of different operation modes, and their main pros and cons are also analysed accordingly. Secondly, technical contributions are reviewed from three aspects: battery modelling, online parameters identification, and SOP estimation. Thirdly, SOP testing methods are discussed, according to their accuracy and efficiency. Finally, the challenges and outlooks are presented to inspire researchers in this field for further developments in the future.

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Online peak power prediction based on a parameter and state estimator for lithium-ion batteries in electric vehicles

Energy ◽

10.1016/j.energy.2014.02.009 ◽

2014 ◽

Vol 66 ◽

pp. 766-778 ◽

Cited By ~ 53

Author(s):

Lei Pei ◽

Chunbo Zhu ◽

Tiansi Wang ◽

Rengui Lu ◽

C.C. Chan

Keyword(s):

Lithium Ion Batteries ◽

Electric Vehicles ◽

Peak Power ◽

Lithium Ion ◽

State Estimator ◽

Power Prediction

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Advances of 2nd Life Applications for Lithium Ion Batteries from Electric Vehicles Based on Energy Demand

Sustainability ◽

10.3390/su13105726 ◽

2021 ◽

Vol 13 (10) ◽

pp. 5726

Author(s):

Aleksandra Wewer ◽

Pinar Bilge ◽

Franz Dietrich

Keyword(s):

Life Cycle ◽

Lithium Ion Batteries ◽

Electric Vehicles ◽

Energy Demand ◽

Lithium Ion ◽

Life Cycles ◽

Future Research ◽

Research Areas ◽

Study Results ◽

The Impact

Electromobility is a new approach to the reduction of CO2 emissions and the deceleration of global warming. Its environmental impacts are often compared to traditional mobility solutions based on gasoline or diesel engines. The comparison pertains mostly to the single life cycle of a battery. The impact of multiple life cycles remains an important, and yet unanswered, question. The aim of this paper is to demonstrate advances of 2nd life applications for lithium ion batteries from electric vehicles based on their energy demand. Therefore, it highlights the limitations of a conventional life cycle analysis (LCA) and presents a supplementary method of analysis by providing the design and results of a meta study on the environmental impact of lithium ion batteries. The study focuses on energy demand, and investigates its total impact for different cases considering 2nd life applications such as (C1) material recycling, (C2) repurposing and (C3) reuse. Required reprocessing methods such as remanufacturing of batteries lie at the basis of these 2nd life applications. Batteries are used in their 2nd lives for stationary energy storage (C2, repurpose) and electric vehicles (C3, reuse). The study results confirm that both of these 2nd life applications require less energy than the recycling of batteries at the end of their first life and the production of new batteries. The paper concludes by identifying future research areas in order to generate precise forecasts for 2nd life applications and their industrial dissemination.

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