Publications
7 results found
Pan Y, Wang H, Brandon NP, 2022, A fast two-phase non-isothermal reduced-order model for accelerating PEM fuel cell design development, International Journal of Hydrogen Energy, Vol: 47, Pages: 38774-38792, ISSN: 0360-3199
A reduced-order model (ROM) is developed for proton exchange membrane fuel cells (PEMFCs) considering the non-isothermal two-phase effects, with the goal of enhancing computational efficiency and thus accelerating fuel cell design development. Using analytical order reduction and approximation methods, the fluxes and source terms in conventional 1D conservation equations are reduced to six computing nodes at the interfaces between each cell component. The errors associated with order reduction are minimized by introducing new approximation methods for the potential distribution, the transport properties, and the membrane hydration status. The trade-off between model accuracy and computational efficiency is studied by comparing the simulation results and computational times of the new model with a full 1D model. The new model is nearly two orders of magnitude faster without sacrificing too much accuracy (<4% difference) compared to the 1D model. The new model is then used to analyze the influence of the membrane electrode assembly (MEA) design on cell performance and internal state distributions, offering insights into MEA structural optimization. The model can be readily extended to account for more detailed physico-chemical processes, such as Knudsen diffusion or the influence of micro-porous layers, and it can be an effective tool for understanding and designing PEMFCs.
Yang S, Zhou S, Zhou X, et al., 2022, All-climate state-of-charge estimation and equilibrium management for lithium-ion batteries based on diffusion equivalent model, JOURNAL OF ENERGY STORAGE, Vol: 52, ISSN: 2352-152X
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- Citations: 1
Pan Y, Wang H, Brandon N, 2021, Gas diffusion layer degradation in proton exchange membrane fuel cells: Mechanisms, characterization techniques and modelling approaches, Journal of Power Sources, Vol: 513, ISSN: 0378-7753
Proton exchange membrane fuel cells (PEMFCs) have been considered as a promising power source for electric vehicles. However, the widespread use of PEMFCs requires a significant improvement in durability. As a key component of PEMFCs, gas diffusion layer (GDL) does not only provide a mechanical support for other fuel cell components, but also governs the mass, heat, and electron transport that directly affect cell performance. In this paper, the latest research progress of GDL durability is reviewed from three aspects: degradation mechanisms, experimental methods, and modelling approaches. The six degradation modes of GDLs, namely chemical oxidation, electrochemical carbon corrosion, freezing/thawing, mechanical degradation, material dissolution and erosion by gas flow are discussed under different cell operating conditions. Experimental techniques, including the long-term and accelerated stress tests (AST) and methods for measuring property deterioration are then introduced. Several AST protocols have been developed to decouple the above degradation modes, but few have tried to relate these tests with GDL degradation in practice. Modelling approaches relating to GDL degradation are also covered. Although various types of models have been developed for multiple purposes, a complete model from the mechanistic level to the cell performance is still missing.
Yang S, Zhou S, Hua Y, et al., 2021, A parameter adaptive method for state of charge estimation of lithium-ion batteries with an improved extended Kalman filter., Scientific Reports, Vol: 11, Pages: 1-15, ISSN: 2045-2322
An accurate state of charge (SOC) estimation in battery management systems (BMS) is of crucial importance to guarantee the safe and effective operation of automotive batteries. However, the BMS consistently suffers from inaccuracy of SOC estimation. Herein, we propose a SOC estimation approach with both high accuracy and robustness based on an improved extended Kalman filter (IEKF). An equivalent circuit model is established, and the simulated annealing-particle swarm optimization (SA-PSO) algorithm is used for offline parameter identification. Furthermore, improvements have been made with noise adaptation, a fading filter and a linear-nonlinear filtering based on the traditional EKF method, and rigorous mathematical proof has been carried out accordingly. To deal with model mismatch, online parameter identification is achieved by a dual Kalman filter. Finally, various experiments are performed to validate the proposed IEKF. Experimental results show that the IEKF algorithm can reduce the error to 2.94% under dynamic stress test conditions, and robustness analysis is verified with noise interference, hence demonstrating its practicability for extending to state estimation of battery packs applied in real-world operating conditions.
Pan Y-W, Hua Y, Zhou S, et al., 2020, A computational multi-node electro-thermal model for large prismatic lithium-ion batteries, Journal of Power Sources, Vol: 459, ISSN: 0378-7753
During operation of large prismatic lithium-ion batteries, temperature heterogeneities are aggravated which affect the performance, lifetime and safety of the cells and packs. Therefore, an accurate model to predict the evolution of temperature profiles in a cell is essential for effective thermal management. In this paper, a pseudo 3D coupled multi-node electro-thermal model is presented for real-time prediction of the heterogeneous temperature field evolution on the surface and inside the battery. The model consists of two parts: a heat generation model based on a second-order equivalent-circuit model and a multi-node heat transfer model based on the battery geometry. Three types of nodes are adopted to describe the thermal characteristics of various components of the cell. Simulation results show that the proposed model has a great consistency with finite element method, and its computational cost is reduced by 90%. The validity of the coupled electrical and thermal model is also demonstrated experimentally for a 105 Ah prismatic cell applying wide ranges of temperature and SOC. The maximum error is less than 2 K throughout the cycles. The proposed model holds a great potential for online temperature estimation in advanced lithium-ion battery thermal management system design.
He Y, He R, Guo B, et al., 2020, Modeling of Dynamic Hysteresis Characters for the Lithium-Ion Battery, JOURNAL OF THE ELECTROCHEMICAL SOCIETY, Vol: 167, ISSN: 0013-4651
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- Citations: 17
Yang S-C, Hua Y, Qiao D, et al., 2019, A coupled electrochemical-thermal-mechanical degradation modelling approach for lifetime assessment of lithium-ion batteries, ELECTROCHIMICA ACTA, Vol: 326, ISSN: 0013-4686
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- Citations: 53
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