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Battery degradation is a complex physicochemical process that strongly depends on operating conditions. We present a model-based analysis of lithium-ion battery degradation in a stationary photovoltaic battery system. We use a multi-scale multi-physics model of a graphite/lithium iron phosphate (LiFePO4, LFP) cell including solid electrolyte interphase (SEI) formation. The cell-level model is dynamically coupled to a system-level model consisting of photovoltaics (PV), inverter, load, grid interaction, and energy management system, fed with historic weather data. Simulations are carried out for two load scenarios, a single-family house and an office tract, over annual operation cycles with one-minute time resolution. As key result, we show that the charging process causes a peak in degradation rate due to electrochemical charge overpotentials. The main drivers for cell ageing are therefore not only a high state of charge (SOC), but the charging process leading towards high SOC. We also show that the load situation not only influences system parameters like self-sufficiency and self-consumption, but also has a significant impact on battery ageing. We assess reduced charge cut-off voltage as ageing mitigation strategy.
Combined heat and power production (CHP) based on solid oxide fuel cells (SOFC) is a very promising technology to achieve high electrical efficiency to cover power demand by decentralized production. This paper presents a dynamic quasi 2D model of an SOFC system which consists of stack and balance of plant and includes thermal coupling between the single components. The model is implemented in Modelica® and validated with experimental data for the stack UI-characteristic and the thermal behavior. The good agreement between experimental and simulation results demonstrates the validity of the model. Different operating conditions and system configurations are tested, increasing the net electrical efficiency to 57% by implementing an anode offgas recycle rate of 65%. A sensitivity analysis of characteristic values of the system like fuel utilization, oxygen-to-carbon ratio and electrical efficiency for different natural gas compositions is carried out. The result shows that a control strategy adapted to variable natural gas composition and its energy content should be developed in order to optimize the operation of the system.
Silicon (Si) has turned out to be a promising active material for next‐generation lithium‐ion battery anodes. Nevertheless, the issues known from Si as electrode material (pulverization effects, volume change etc.) are impeding the development of Si anodes to reach market maturity. In this study, we are investigating a possible application of Si anodes in low‐power printed electronic applications. Tailored Si inks are produced and the impact of carbon coating on the printability and their electrochemical behavior as printed Si anodes is investigated. The printed Si anodes contain active material loadings that are practical for powering printed electronic devices, like electrolyte gated transistors, and are able to show high capacity retentions. A capacity of 1754 mAh/gSi is achieved for a printed Si anode after 100 cycles. Additionally, the direct applicability of the printed Si anodes is shown by successfully powering an ink‐jet printed transistor.
Mass transfer phenomena in membrane fuel cells are complex and diversified because of the presence of complex transport pathways including porous media of very different pore sizes and possible formation of liquid water. Electrochemical impedance spectroscopy, although allowing valuable information on ohmic phenomena, charge transfer and mass transfer phenomena, may nevertheless appear insufficient below 1 Hz. Use of another variable, that is, back pressure, as an excitation variable for electrochemical pressure impedance spectroscopy is shown here a promising tool for investigations and diagnosis of fuel cells.
Model-based analysis of Electrochemical Pressure Impedance Spectroscopy (EPIS) for PEM Fuel Cells
(2019)
Electrochemical impedance spectroscopy (EIS) is a widely-used diagnostic technique to characterize electrochemical processes. It is based on the dynamic analysis of two electrical observables, that is, current and voltage. Electrochemical cells with gaseous reactants or products, in particular fuel cells, offer an additional observable, that is, the gas pressure. The dynamic coupling of current or voltage with gas pressure gives rise to a number of additional impedance definitions, for which we have previously introduced the term electrochemical pressure impedance spectroscopy (EPIS) [1,2]. EPIS shows a particular sensitivity towards transport processes of gas-phase or dissolved species, in particular, diffusion coefficients and transport pathway lengths. It is as such complementary to standard EIS, which is mainly sensitive towards electrochemical processes. First EPIS experiments on PEM fuel cells have recently been shown [3].
We present a detailed modeling and simulation analysis of EPIS of a PEM fuel cell. We use a 1D+1D continuum model of a fuel/air channel pair with GDL and MEA. Backpressure is dynamically varied, and the resulting simulated oscillation in cell voltage is evaluated to yield the ▁Z_( V⁄p_ca ) EPIS signal. Results are obtained for different transport situations of the fuel cell, giving rise to very complex EPIS shapes in the Nyquist plot. This complexity shows the necessity of model-based interpretation of the complex EPIS shapes. Based on the simulation results, specific features in the EPIS spectra can be assigned to different transport domains (gas channel, GDL, membrane water transport).
Lithium-ion batteries exhibit a well-known trade-off between energy and power, which is problematic for electric vehicles which require both high energy during discharge (high driving range) and high power during charge (fast-charge capability). We use two commercial lithium-ion cells (high-energy [HE] and high-power) to parameterize and validate physicochemical pseudo-two-dimensional models. In a systematic virtual design study, we vary electrode thicknesses, cell temperature, and the type of charging protocol. We are able to show that low anode potentials during charge, inducing lithium plating and cell aging, can be effectively avoided either by using high temperatures or by using a constant-current/constant-potential/constant-voltage charge protocol which includes a constant anode potential phase. We introduce and quantify a specific charging power as the ratio of discharged energy (at slow discharge) and required charging time (at a fast charge). This value is shown to exhibit a distinct optimum with respect to electrode thickness. At 35°C, the optimum was achieved using an HE electrode design, yielding 23.8 Wh/(min L) volumetric charging power at 15.2 min charging time (10% to 80% state of charge) and 517 Wh/L discharge energy density. By analyzing the various overpotential contributions, we were able to show that electrolyte transport losses are dominantly responsible for the insufficient charge and discharge performance of cells with very thick electrodes.
Simulation-based degradation assessment of lithium-ion batteries in a hybrid electric vehicle
(2017)
The insufficient lifetime of lithium-ion batteries is one of the major cost driver for mobile applications. The battery pack in vehicles is one of the most expensive single components that practically must be excluded from premature replacement (i.e., before the life span of the other components end). Battery degradation is a complex physicochemical process that strongly depends on operating condition and environment. We present a simulation-based analysis of lithium-ion battery degradation during operation with a standard PHEV test cycle. We use detailed multiphysics (extended Newman-type) cell models that allow the assessment of local electrochemical potential, species and temperature distributions as driving forces for degradation, including solid electrolyte interphase (SEI) formation [1]. Fig. 1 shows an exemplary test cycle and the predicted resulting spatially-averaged SEI formation rate. We apply a time-upscaling approach to extrapolate the degradation analysis over long time scales, keeping physical accuracy while allowing end-of-life assessment [2]. Results are presented for lithium-ion battery cells with graphite/LFP chemistry. The behavior of these cells in terms of degradation propensity, performance, state of charge and other internal states is predicted during long-term cycling. State of health (SOH) is quantified as capacity fade and internal resistance increase as function of operation time.
The durability of polymer electrolyte membrane fuel cells (PEMFC) is governed by a nonlinear coupling between system demand, component behavior, and physicochemical degradation mechanisms, occurring on timescales from the sub-second to the thousand-hour. We present a simulation methodology for assessing performance and durability of a PEMFC under automotive driving cycles. The simulation framework consists of (a) a fuel cell car model converting velocity to cell power demand, (b) a 2D multiphysics cell model, (c) a flexible degradation library template that can accommodate physically-based component-wise degradation mechanisms, and (d) a time-upscaling methodology for extrapolating degradation during a representative load cycle to multiple cycles. The computational framework describes three different time scales, (1) sub-second timescale of electrochemistry, (2) minute-timescale of driving cycles, and (3) thousand-hour-timescale of cell ageing. We demonstrate an exemplary PEMFC durability analysis due to membrane degradation under a highly transient loading of the New European Driving Cycle (NEDC).