Method for initializing the charge state of a battery
View Patent ↗A method for estimating the charge state of a battery includes initializing the charge state, including estimating an initial charge state value. The initializing includes: receiving a stored charge state value for a sleep mode time of the battery, computing a charge state value from a measurement of the no-load voltage at the terminals of the battery at a wake-up time of the battery, and computing an error in the measurement of the no-load voltage due to the relaxation of the battery. The error is computed as a function of the current temperature of the battery and of a target relaxation duration modelled for each temperature. The initial value of the charge state is computed based on a comparison between the recorded and computed charge state values and as a function of the error.
1. A method for estimating a state of charge of a battery, comprising:
initializing the state of charge of the battery, including estimating an initial value of the state of charge, the initializing comprising:
receiving a stored state-of-charge value of the battery when the battery enters sleep mode,
calculating a state-of-charge value using a measurement of a no-load voltage at terminals of the battery when the battery wakes, and
calculating an error in the measurement of the no-load voltage due to relaxation of the battery, in which the error is calculated as a function of a current temperature of the battery and a target relaxation time of the battery modeled for each temperature, wherein
the estimating of the initial value of the state of charge is calculated based on a comparison between the stored values and calculated values of the state of charge and as a function of the calculated error,
the calculating the error caused by relaxation comprises:
storing map data correlating a given state of charge with a given no-load voltage of the battery, for a given temperature of the battery,
determining a maximum error in the measurement of the no-load voltage corresponding to the error between the battery voltage on waking for a minimum relaxation time and the battery voltage on waking for the target relaxation time,
providing error calibration data describing a variation of a margin of error in the state of charge in relation to a state-of-charge value provided by the map data, as a function of the maximum error,
designating a plurality of zones within the error calibration data, each of the zones including a predefined range of the state-of-charge values,
determining a zone of the plurality of zones that includes the state-of-charge value provided by the map data,
selecting maximum error data describing a maximum value of the variation of the margin of error in the state of charge within the zone, and
calculating the error caused by relaxation using the no-load voltage measurement when the battery wakes and the error calibration data maximum error data for the zone, and
the initializing further comprises determining a state of relaxation of the battery on waking.
2. The method as claimed in claim 1 , wherein the estimating the initial value of the state of charge is calculated as a function of whether a polarization direction of the battery corresponds to charging or discharging when entering sleep mode.
3. The method as claimed in claim 2 , wherein the estimating the initial value of the state of charge is calculated in consideration of a parameter representing the actual sleeping time of the battery in relation to the target relaxation time of the battery.
4. The method as claimed in claim 3 , wherein, when the polarization direction corresponds to discharging when entering sleep mode and the stored state-of-charge value (SOCmem) at that instant is equal to or greater than the calculated state-of-charge value (SOCocv) on waking, the estimate of the initial state-of-charge value (SOCini) is calculated as follows:
SOCini =min( SOCmem,SOCocv+Err ),
otherwise:
SOCini =(1− a )· SOCocv+a ·( SOCocv+Err ),
with Err being the calculated error, and the parameter (a) varying between 0 when the sleeping time of the battery is equal to the target relaxation time of the battery, and 1 when the sleeping time of the battery is equal to a minimum time required between a battery sleep request and a battery wake request.
5. The method as claimed in claim 3 , wherein, when the polarization direction corresponds to charging when entering sleep mode and the stored state-of-charge value (SOCmem) at that instant is equal to or less than the calculated state-of-charge value (SOCocv) on waking, the estimate of the initial state-of-charge value (SOCini) is calculated as follows:
SOCini =max( SOCmem, SOCocv−Err ),
otherwise:
SOCini =(1− a )· SOCocv+a ·( SOCocv−Err ),
with Err being the calculated error, and the parameter (a) varying between 0 when the sleeping time of the battery is equal to the target relaxation time of the battery, and 1 when the sleeping time of the battery is equal to a minimum time required between a battery sleep request and a battery wake request.
6. The method as claimed in claim 3 , wherein, when the polarization direction corresponds to discharging when entering sleep mode and the stored state-of-charge value (SOCmem) at that instant is equal to or greater than the calculated state-of-charge value (SOCocv) on waking, the estimate of the initial state-of-charge value (SOCini) is calculated as follows: SOCini=min(SOCmem, SOCocv+Err),
with Err being the calculated error.
7. The method as claimed in claim 3 , wherein, when the polarization direction corresponds to charging when entering sleep mode and the stored state-of-charge value (SOCmem) at that instant is equal to or less than the calculated state-of-charge value (SOCocv) on waking, the estimate of the initial state-of-charge value (SOCini) is calculated as follows: SOCini=max(SOCmem, SOCocv−Err),
with Err being the calculated error.
8. The method as claimed in claim 2 , wherein, when the polarization direction corresponds to discharging when entering sleep mode and the stored state-of-charge value (SOCmem) at that instant is less than the calculated state-of-charge value (SOCocv) on waking, the estimate of the initial state-of-charge value (SOCini) is calculated as follows: SOCini=(SOCocv+(SOCocv+Err))/2,
with Err being the calculated error.
9. The method as claimed in claim 2 , wherein, when the polarization direction corresponds to charging when entering sleep mode and the stored state-of-charge value (SOCmem) at that instant is greater than the calculated state-of-charge value (SOCocv) on waking, the estimate of the initial state-of-charge value (SOCini) is calculated as follows: SOCini=(SOCocv+(SOCocv−Err))/2,
with Err being the calculated error.
10. The method as claimed in claim 1 , wherein the error calibration data further describes a variation of a margin of error in the state of charge in relation to a state-of-charge value provided by the map data, as a function of whether the relaxation period follows battery charge or discharge polarization.
11. A management device for a battery, comprising:
processing circuitry configured to initialize a state of charge of the battery, including estimating an initial value of the state of charge, the initializing comprising:
receiving a stored state-of-charge value of the battery when the battery enters sleep mode,
calculating a state-of-charge value using a measurement of a no-load voltage at terminals of the battery when the battery wakes, and
calculating an error in the measurement of the no-load voltage due to relaxation of the battery, in which the error is calculated as a function of a current temperature of the battery and a target relaxation time of the battery modeled for each temperature, wherein
the estimating of the initial value of the state of charge is calculated based on a comparison between the stored values and calculated values of the state of charge and as a function of the calculated error,
the calculating the error caused by relaxation comprises:
storing map data correlating a given state of charge with a given no-load voltage of the battery, for a given temperature of the battery,
determining a maximum error in the measurement of the no-load voltage corresponding to the error between the battery voltage on waking for a minimum relaxation time and the battery voltage on waking for the target relaxation time,
providing error calibration data describing a variation of a margin of error in the state of charge in relation to a state-of-charge value provided by the map data, as a function of the maximum error,
designating a plurality of zones within the error calibration data, each of the zones including a predefined range of the state-of-charge values,
determining a zone of the plurality of zones that includes the state-of-charge value provided by the map data,
selecting maximum error data describing a maximum value of the variation of the margin of error in the state of charge within the zone, and
calculating the error caused by relaxation using the no-load voltage measurement when the battery wakes and the maximum error data for the zone, and
the initializing further comprises determining a state of relaxation of the battery on waking.
12. The management device according to claim 11 , wherein the battery is a traction battery of an electric vehicle.
13. A rechargeable hybrid or electric motor vehicle, comprising:
the management device as claimed in claim 11 .
14. The management device as claimed in claim 11 , wherein the error calibration data further describes a variation of a margin of error in the state of charge in relation to a state-of-charge value provided by the map data, as a function of whether the relaxation period follows battery charge or discharge polarization.