Noshin Omar

Bio: Noshin Omar is an academic researcher from Vrije Universiteit Brussel. The author has contributed to research in topics: Battery (electricity) & Lithium. The author has an hindex of 40, co-authored 154 publications receiving 5630 citations. Previous affiliations of Noshin Omar include Erasmus University College & Hogeschool-Universiteit Brussel.

Critical review of state of health estimation methods of Li-ion batteries for real applications

Abstract: Lithium-ion battery packs in hybrid and electric vehicles, as well as in other traction applications, are always equipped with a Battery Management System (BMS). The BMS consists of hardware and software for battery management including, among others, algorithms determining battery states. The accurate and reliable State of Health (SOH) estimation is a challenging issue and it is a core factor of a battery energy storage system. In this paper, battery SOH monitoring methods are reviewed. To this end, different scientific and technical literature is studied and the respective approaches are classified in specific groups. The groups are organized in terms of the way the method is carried out: Experimental Techniques or Adaptive Models. Not only strengths and weaknesses for the use in online BMS applications are reviewed but also their accuracy and precision is studied. At the end of the document a potential, new and promising via in order to develop a methodology to estimate the SOH in real applications is detailed.

Cost Projection of State of the Art Lithium-Ion Batteries for Electric Vehicles Up to 2030

Abstract: The negative impact of the automotive industry on climate change can be tackled by changing from fossil driven vehicles towards battery electric vehicles with no tailpipe emissions. However their adoption mainly depends on the willingness to pay for the extra cost of the traction battery. The goal of this paper is to predict the cost of a battery pack in 2030 when considering two aspects: firstly a decade of research will ensure an improvement in material sciences altering a battery’s chemical composition. Secondly by considering the price erosion due to the production cost optimization, by maturing of the market and by evolving towards to a mass-manufacturing situation. The cost of a lithium Nickel Manganese Cobalt Oxide (NMC) battery (Cathode: NMC 6:2:2 ; Anode: graphite) as well as silicon based lithium-ion battery (Cathode: NMC 6:2:2 ; Anode: silicon alloy), expected to be on the market in 10 years, will be predicted to tackle the first aspect. The second aspect will be considered by combining process-based cost calculations with learning curves, which takes the increasing battery market into account. The 100 dollar/kWh sales barrier will be reached respectively between 2020-2025 for silicon based lithium-ion batteries and 2025–2030 for NMC batteries, which will give a boost to global electric vehicle adoption.

Passive and active battery balancing comparison based on MATLAB simulation

Abstract: Battery systems are affected by many factors, the most important one is the cells unbalancing. Without the balancing system, the individual cell voltages will differ over time, battery pack capacity will decrease quickly. That will result in the fail of the total battery system. Thus cell balancing acts an important role on the battery life preserving. Different cell balancing methodologies have been proposed for battery pack. This paper presents a review and comparisons between the different proposed balancing topologies for battery string based on MATLAB/Simulink® simulation. The comparison carried out according to circuit design, balancing simulation, practical implementations, application, balancing speed, complexity, cost, size, balancing system efficiency, voltage/current stress … etc.

Multi-level conversion : high voltage choppers and voltage-source inverters

Abstract: The authors discuss high-voltage power conversion. Conventional series connection and three-level voltage source inverter techniques are reviewed and compared. A novel versatile multilevel commutation cell is introduced: it is shown that this topology is safer and more simple to control, and delivers purer output waveforms. The authors show how this technique can be applied to either choppers or voltage-source inverters and generalized to any number of switches.<>

Data-driven prediction of battery cycle life before capacity degradation

Abstract: Accurately predicting the lifetime of complex, nonlinear systems such as lithium-ion batteries is critical for accelerating technology development. However, diverse aging mechanisms, significant device variability and dynamic operating conditions have remained major challenges. We generate a comprehensive dataset consisting of 124 commercial lithium iron phosphate/graphite cells cycled under fast-charging conditions, with widely varying cycle lives ranging from 150 to 2,300 cycles. Using discharge voltage curves from early cycles yet to exhibit capacity degradation, we apply machine-learning tools to both predict and classify cells by cycle life. Our best models achieve 9.1% test error for quantitatively predicting cycle life using the first 100 cycles (exhibiting a median increase of 0.2% from initial capacity) and 4.9% test error using the first 5 cycles for classifying cycle life into two groups. This work highlights the promise of combining deliberate data generation with data-driven modelling to predict the behaviour of complex dynamical systems. Accurately predicting battery lifetime is difficult, and a prediction often cannot be made unless a battery has already degraded significantly. Here the authors report a machine-learning method to predict battery life before the onset of capacity degradation with high accuracy.

Sustainable Recycling Technology for Li-Ion Batteries and Beyond: Challenges and Future Prospects.

Abstract: Tremendous efforts are being made to develop electrode materials, electrolytes, and separators for energy storage devices to meet the needs of emerging technologies such as electric vehicles, decarbonized electricity, and electrochemical energy storage. However, the sustainability concerns of lithium-ion batteries (LIBs) and next-generation rechargeable batteries have received little attention. Recycling plays an important role in the overall sustainability of future batteries and is affected by battery attributes including environmental hazards and the value of their constituent resources. Therefore, recycling should be considered when developing battery systems. Herein, we provide a systematic overview of rechargeable battery sustainability. With a particular focus on electric vehicles, we analyze the market competitiveness of batteries in terms of economy, environment, and policy. Considering the large volumes of batteries soon to be retired, we comprehensively evaluate battery utilization and recycling from the perspectives of economic feasibility, environmental impact, technology, and safety. Battery sustainability is discussed with respect to life-cycle assessment and analyzed from the perspectives of strategic resources and economic demand. Finally, we propose a 4H strategy for battery recycling with the aims of high efficiency, high economic return, high environmental benefit, and high safety. New challenges and future prospects for battery sustainability are also highlighted.