madrid2i

Resumen

[0001] The invention relates to a method for diagnosing batteries in dynamic environments which allows assuring high battery reliability for implementing a predictive maintenance plan, and which basically comprises the steps of measuring the impedance of groups of cells or modules of the batteries, subsequently applying a correction of said impedance as a function of temperature and then a correction which takes into account the effect that the ageing of the batteries has on said modules or groups of cells.

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1. Method for diagnosing batteries in dynamic environments, characterized in that it comprises the stages of: - measuring the impedance at the module level; - obtaining the corrected impedance by means of applying a correction algorithm for correcting said impedance with the temperature; and - applying a second algorithm to the impedance corrected by means of the previous stage such that the effect that the ageing of the batteries has on said corrected impedance is taken into account. 2. Method for diagnosing batteries in dynamic environments according to claim 1, characterized in that the correction algorithm for correcting impedance with the temperature comprises the stages of: - measuring the impedance of several modules of batteries of the same model in different life cycle states; - measuring the impedance of each module at different temperatures; - obtaining, for each of the modules, the family of straight lines of impedance as a function of temperature, according to: Z = m i ⋅ T + a i <img class="EMIRef" id="464482605-ib0021" /> - obtaining the set of straight lines relating impedance Z and slope m<i> for each T<j> value, according to: Z = b j ⋅ m + k <img class="EMIRef" id="464482605-ib0022" /> - obtaining the value of b<j> , consisting of taking the set of values b<j> produced by each T<j> as a linear variation according to: b j = α ⋅ T + β <img class="EMIRef" id="464482605-ib0023" /> - determining, for each fixed T value, the value of b and obtaining the α and β values; and - obtaining the expression of the compensation to be applied by joining the expressions (b) and (c), according to: m m ⁢ Ω / ° ⁢ C = Z - k α ⁢ T + β <img class="EMIRef" id="464482605-ib0024" /> 3. Method for diagnosing batteries in dynamic environments according to claim 2, characterized in that the different life cycle states in which the impedance is measured comprise the initial state, the end of their service life and one or several intermediate states. 4. Method for diagnosing batteries in dynamic environments according to the previous claims, characterized in that obtaining the corrected impedance comprises the steps of: - fixing an arbitrary temperature; - taking samples of or measuring the impedance of a module; - measuring the temperature T in the terminals of the module in which the impedance Z was just measured; - applying the correction algorithm for correcting impedance with the temperature to the experimentally measured values of Z and T to obtain the correction Z<*> in (mΩ/ºC) according to: Z * = Z - m ⁢ T - T 0 <img class="EMIRef" id="464482605-ib0025" /> - obtaining by substituting in (d): Z * = Z - Z - k α ⁢ T + β ⁢ T - T 0 <img class="EMIRef" id="464482605-ib0026" /> 5. Method for diagnosing batteries in dynamic environments according to the previous claims, characterized in that the second algorithm applied to the corrected impedance comprises the stages of: - measuring the impedance of a representative amount of modules in service of the same type and model, applying the correction algorithm for correcting impedance; - transforming the corrected impedance Z* into a variable X which follows a normal distribution; - obtaining the normal distribution of the transformed variable X; - calculating the maximum likelihood estimators of the distribution of the variable X; - fixing the upper limit of the confidence interval for the variable X from the maximum likelihood estimators, - transforming the limits of the confidence interval for the variable X into the variable Z* by means of the corresponding inverse transform; and - comparing the corrected impedance values Z* previously obtained with the upper limit of the confidence interval and performing the diagnosis of "usable - non-usable" according to whether or not said measured value is greater than the mentioned upper limit. 6. Method for diagnosing batteries in dynamic environments according to claim 5, characterized in that the statistical transformation method for transforming the corrected impedance Z* into a variable X which follows a normal distribution is the Box-Cox transformation. 7. Method for diagnosing batteries in dynamic environments according to claim 1, characterized in that it additionally comprises checking if an internal short circuit has occurred between any of the plates forming part of each cell of the module. 8. Method for diagnosing batteries in dynamic environments according to claim 7, characterized in that it comprises calculating the relationship between the measured voltage with the battery being discharged and the measurement with the battery when it has no load such that if the voltage measurement in the module of the battery when it has no load is less than a calculated value said module can be discarded as it is defective.

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