Real-time state of charge estimation of electrochemical model for lithium-ion battery

This paper proposes the real-time Kalman filter based observer for Lithium-ion concentration estimation for the electrochemical battery model. Since the computation limitation of real-time battery management system (BMS) micro-processor, the battery model which is utilized in observer has been further simplified. In this paper, the Kalman filter based observer is applied on a reduced order model of single particle model to reduce computational burden for real-time applications. Both solid phase surface lithium concentration and battery state of charge (SoC) can be estimated with real-time capability. Software simulation results and the availability comparison of observers in different Hardware-in- the-loop simulation setups demonstrate the performance of the proposed method in state estimation and real-time application

System identification of lithium-ion battery dynamics : from characterisation to application

To alleviate range anxiety among electric vehicle (EV) owners, the accuracy of lithium-ion battery (LIB) mathematical models in the low state of charge (SOC) range must be enhanced. A battery model that is easy to parameterise while maintaining accuracy over the entire SOC range is required in sophisticated battery management algorithms. This thesis addresses this knowledge gap via system identification methods of characterisation, identification, and application. The level of non-linearity over different SOCs is first studied by using random phase odd-multisine signals, and applied on the Doyle-Fuller-Newman (DFN) model and a three-electrode experimental set-up of a commercial 5Ah cylindrical 21700 LIB cell. The charge transfer coefficient is determined as the most sensitive parameter towards battery nonlinearity and with an asymmetrical Butler-Volmer kinetic the model nonlinear response provided good agreement against experimental data. The cathode even order nonlinearity is the main contributor towards the battery voltage nonlinearity while the anode starts to dominate at very low SOC. Utilising the newly proposed characterisation method, a non-linear equivalent circuit model with diffusion dynamics (NLECM-di↵), which phenomenologically describes the main electrochemical behaviours, such as ohmic, charge-transfer kinetics, and diffusion processes, is identified. Compared to the parameterisation challenge of electrochemical models, the NLECM-di↵ does not rely on geometrical parameter and all parameters are determined from the measured current and voltage signals. The NLECM-di↵ is around 50% more accurate than a conventional ECM and is comparable to the single particle model with electrolyte model (SPMe). When simulating driving cycles and long duration discharges, the dominant voltage loss changes from ohmic to the diffusion losses, and the characteristic of the negative electrode is determined as the primary reason for the low-SOC-error. The last part of this thesis presents three case studies of model application as part of the project ‘Virtually Connected Hybrid Vehicle (VCHV)’. The SPMe and the NLECM-di↵ models were demonstrated in Hardware-in-the-Loop (HIL) and therefore merit consideration for EV applications

Biomass-derived carbon nanostructures and their applications as electrocatalysts for hydrogen evolution and oxygen reduction/evolution

Biomass derived electrocatalysts with rationally designed activity, selectivity, and stability present a major sustainable approach for the electrochemical production of fuels and value-added chemicals. This review presents recent advances in the field of biomass-derived electrocatalytic nanostructures for the hydrogen evolution reaction (HER) and the oxygen reduction and evolution reactions (oxygen reduction reaction and oxygen evolution reaction), that are subject of major research efforts, as well as public and private investment, as they will play a crucial role in the energy transition and in achieving net zero carbon emissions. The review summarises experimental and theoretical investigations aiming at tuning electrocatalytic performances of sustainable C-based nanostructured materials, and present opportunities for future commercialization of innovative energy materials and applications. In reviewing relevant literature in the field, we focus on the correlation between electrocatalytic activity/selectivity and synthesis methods, composition, physical chemical characteristics, in the attempt to uncover a clear structure-activity relationship. Furthermore, this study provides a critical comparison of the different electrocatalysts in light of their catalytic mechanisms, limiting phenomena, and practical applications for sustainable future technologies

Understanding non-linearity in electrochemical systems using multisine-based non-linear characterization

Background: With the development of advanced characterization techniques, lithium-ion battery non-linearities have recently gained increased attention which can benefit battery health diagnosis and ageing mechanism identification. In comparison to conventional single sine wave-based methods, the multisine-based non-linear characterization method has the advantage of capturing the dynamic voltage response within a short testing duration, and therefore has further development potential for on-board applications. However, understanding lithium-ion battery electrochemical processes that contribute to battery non-linearities is still unclear. Methods: In this paper, the sensitivity of the Doyle–Fuller–Newman model parameters are analysed in the frequency domain to investigate the electrochemical processes that contribute to the non-linear dynamics of the voltage response. To begin with, the non-linearities of the Doyle–Fuller–Newman model with validated parameters are characterized and compared to experimental data from a commercial cell. This demonstrated a significant difference between the mathematical model and the non-linearities determined experimentally. Then, a global sensitivity analysis is applied to determine the most sensitive parameter contributing to battery non-linearities. Finally, the appropriate value of the most sensitive parameter which results in the closest non-linear response to the commercial battery is estimated through minimizing the root mean square error. Results: The results show that the charge transfer coefficient is the most sensitive parameter contributing to battery non-linearities among the Doyle–Fuller–Newman model parameters. The non-linear response of the Doyle–Fuller–Newman model is validated with good agreement with the experimental results, when the Butler–Volmer kinetic is asymmetrical due to the unequal anodic and cathodic charge transfer coefficients

Selective Synthesis of Fe2O3 and Fe3O4 Nanowires Via a Single Precursor: A General Method for Metal Oxide Nanowires

Hematite (α-Fe2O3) and magnetite (Fe3O4) nanowires with the diameter of about 100 nm and the length of tens of micrometers have been selectively synthesized by a microemulsion-based method in combination of the calcinations under different atmosphere. The effects of the precursors, annealing temperature, and atmosphere on the morphology and the structure of the products have been investigated. Moreover, Co3O4 nanowires have been fabricated to confirm the versatility of the method for metal oxide nanowires

GRIK3 rs490647 is a Common Genetic Variant between Personality and Subjective Well-being in Chinese Han Population

Personality and subjective well-being (SWB) have been suggested to be strongly related in previous studies. This study was intended to confirm the relationship between personality and SWB and tried to seek out the genetic variants which underlie both personality and SWB. The subjects were 890 participants from Chinese Han population. We evaluated their personality using the Big Five Inventory (BFI) and used the Satisfaction With Life Scale (SWLS) to reflect their SWB. Five single nucleotide polymorphisms (SNPs) were selected from the literature (rs1426371, rs2164273, rs322931, rs3756290, rs490647) and genotyped for genetic association study. We found negative correlations between neuroticism and SWB. On the contrary, extraversion and agreeableness were positively associated with SWB. Three SNPs (rs2164273, rs3756290, rs490647) out of the five were found to connect with personality (extraversion, neuroticism, conscientiousness and openness to experience) and rs490647 variants of GRIK3 was also associated with SWB. Individuals carrying G allele at this site were predisposed to have lower risk to be neuroticism and greater chance to be extraverted, open and satisfied with their life. In summary, our study revealed that rs490647 might be a good candidate genetic variant for personality and SWB in Chinese Han population

Understanding of Lithium-ion battery degradation using multisine-based nonlinear characterization method

The nonlinearity of lithium-ion battery voltage response has been recently gained high attention in battery characterization and health diagnosis. The multisine-based nonlinear characterization method has the potential for development as an expedient on-board technique for analyzing nonlinear responses. Despite this, it remains challenging to analyze the effect of aging degradation on LIB nonlinearity. In this study, the odd random-phase multisine method is performed on fresh and aged three-electrode experimental cells. This allowed for the separation of impedance-related linear approximation and odd or even order nonlinearity toward the full-cell voltage into their respective electrodes. The results demonstrate that, as the LIB degrades, the increase of impedance-related linear approximation estimated by the multisine-based method agrees well with the results of conventional EIS. The variation of nonlinearities is demonstrated in relation to the effect of degradation modes. The multisine-based method presents the advantage of simultaneously capturing impedance-related and nonlinearity information. This makes it become a fast diagnostic method that can be implemented in a BMS to quantify the causes of battery degradation, thereby supporting battery utilization optimization and future battery designs

Nanomaterials and technologies for low temperature solid oxide fuel cells : recent advances, challenges and opportunities

Solid oxide fuel cells (SOFCs) show considerable promise for meeting the current ever-increasing energy demand and environmental sustainability requirements because of their high efficiency, low environmental impact, and distinct fuel diversity. In the past few decades, extensive R&D efforts have been focused on lowering operational temperatures in order to decrease the system (stack and balance-of-plant) cost and improve the longevity of operationally useful devices of commercial relevance. Nanomaterials and related nanotechnologies have the potential to improve SOFC performance because of their advantageous functionalities, namely, their enlarged surface area and unique surface and interface properties compared to their microscale analogs. Recently, the use of nanomaterials has increased rapidly, as reflected by the exponential growth in the number of publications since 2002. In this work, we present a comprehensive summary of nanoparticles, nano-thin films and nanocomposites with different crystal phases, morphologies, microstructures, electronic properties, and electrochemical performances for low temperature SOFCs (LT-SOFCs), with focus on efforts to enhance electrical efficiency, to induce novel fundamental properties that are inaccessible in microcrystalline materials, and to promote the commercialization of LT-SOFCs. Recent progress in the applications of many classically or newly chemical and physical nanomaterials and nanofabrication techniques, such as thin film vacuum deposition, impregnation, electrospinning, spark plasma sintering, hard- and soft-template methods, and in-situ nanoparticle surface exsolution are also thoroughly described. The technological and scientific advantages and limitations related to the use of nanomaterials and nanotechnologies are highlighted, along with our expectations for future research within this emerging field.NRF (Natl Research Foundation, S’pore)MOE (Min. of Education, S’pore