NHN Battery
Battery DTU
NHN Battery Component Model
Battery DTU - Model overview
Model Overview
Author / organization: Oliver Gehrke / DTU
Domain: Electrical storage
Intended application: Reproducing the operational constraints imposed by the integrated battery management system
Modelling of spatial aspects: Lumped (single device)
Model dynamics: Quasi-static
Model of computation: Time-continuous
Functional representation: Explicit
Battery DTU - input and output
Input and Output
Input variables :
- P_set [kW]: Requested discharge rate (negative values=battery is requested to charge) of the entire unit, measured at AC terminals
- Q_set [kVAr]: Requested reactive power production (negative values=requested consumption) of the entire unit, measured at AC terminals
Output variables:
- P_inst [kW]: Instantaneous power production/discharge (negative values=power consumption/charge) of the entire unit, measured at AC terminals
- Q_inst [kVAr]: Instantaneous reactive power production (negative values=power consumption) of the entire unit, measured at AC terminals
- SOC [%]: State of charge of the entire battery unit
Battery DTU - related documents
Battery DTU - description
Short Description
Stationary lithium-ion battery unit. As test system configuration, only the simulation model and the BMS controller are required to perform the simulation, i.e. there is no necessity to interact with other models. The test starts at zero POSIX epoch time (=00:00:00 UTC, Jan 1st, 1970) and will run for 24h of simulation time (86400 seconds).
The battery model generally works at lower time resolutions; however, the achievable precision depends on the relationship between the chosen timestep and the duration of the charge/discharge patterns applied to the battery, as well as the length of the entire simulation period. The latter is particularly critical because errors in energy content and battery degradation may accumulate over time.
Present use / development status
The model primarily aims at reproducing the operational constraints imposed by the integrated battery management system while the electrochemical processes are simplified and not modelled in detail (“leaky bucket with linear degradation”). Typical time resolutions are in the order of seconds.
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Batter
Model Details
Domain |
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Intended application (including scale and resolution) | The model primarily aims at reproducing the operational constraints imposed by the integrated battery management system while the electrochemical processes are simplified and not modelled in detail (“leaky bucket with linear degradation”). Typical time resolutions are in the order of seconds. | ||
Modelling of spatial aspects |
The battery is considered as a single lumped component, which provides a certain power or stores a defined amount of energy according to supply and demand. | ||
Model dynamics |
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Model of computation |
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Functional representation |
The model is an equivalent circuit model including lookup tables. |
Input variables (name, type, unit, description) |
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Output variables (name, type, unit, description) |
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Parameters (name, type, unit, description) |
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Internal variables (name, type, unit, description) |
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Internal constants (name, type, unit, description) | dt [s]: Simulation time step (default=10s)
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Model equations | Governing equations | ||
Note:
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Constitutive equations | |||
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Initial conditions |
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Boundary conditions | - | ||
Optional: graphical representation (schematic diagram, state transition diagram, etc.) |
Model Validation | |||
Narrative | This test can be used to validate the stationary battery model by testing for correct response under different active and reactive power limiting conditions, i.e., with the charging or discharging power limited by the maximum inverter current or high SOC derating. The test covers the following elements of the model:
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Test system configuration |
Only the simulation model and the BMS controller are required to perform the simulation, i.e. there is no necessity to interact with other models. The test starts at zero POSIX epoch time (=00:00:00 UTC, Jan 1st, 1970) and will run for 24h of simulation time (86400 seconds).
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Inputs and parameters |
Inputs:
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Control function (optional) | The SOC derating of the battery BMS is defined by the control function provided in the attached file DTU_Battery_BMS.pdf.
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Initial system state |
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Temporal resolution | The test is run at a constant timestep of 10s.
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Evolution of system state |
The plot below shows active and reactive setpoint patterns with different characteristics being applied to the battery. Some of these setpoints exceed the rated capability of the battery. The power drawn at the battery's point of common coupling is a function of power limitations imposed by the battery capability (static), the inverter current limit (dynamic) and limitations imposed by the BMS (dynamic) in certain SOC ranges. The sequence shown below covers the full spectrum of causes for charging power limitations (for a full discussion, see the "Results" section). | ||
Results | The battery validation test moves the battery through the following operating regimes:
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Model harmonization | |||
Narrative | The battery model generally works at lower time resolutions; however, the achievable precision depends on the relationship between the chosen timestep and the duration of the charge/discharge patterns applied to the battery, as well as the length of the entire simulation period. The latter is particularly critical because errors in energy content and battery degradation may accumulate over time. | ||
Test system configuration | Same as in model validation. | ||
Inputs and parameters | The dataset used is the same as in Model Validation; however, P and Q setpoints correspond to the mean of all setpoint values since the previous timestamp (boxcar average): where T is the current timestamp and dt is the timestep length. | ||
Initial system state | Same as in model validation. | ||
Temporal resolution | The test is run at a constant timestep of 1h. | ||
Evolution of system state | Since the test uses the same testing pattern as the validation test, it exhibits the same phenomena, albeit at less detail. The main focus at this lower time resolution (and potentially even lower resolutions) should be on comparing the medium and long-term indicators of battery performance over a more than one cycle: Energy content (related to the state of charge) and battery degradation (related to cycle age). | ||
Results |
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