A method for estimating a battery state of an energy storage system of a vehicle using at least a dual estimator, wherein the energy storage system comprises at least one battery unit, and wherein the dual estimator comprises: - a first estimator comprising a first non-linear observer, the first estimator being configured to estimate at least one battery state of the energy storage system using a prediction model, the first estimator having first tuning parameters, - a second estimator comprising at least one second non-linear observer, the second estimator being configured to track changes around nominal values of a set of battery parameters of the energy storage system, the second estimator having second tuning parameters, a first feedback loop being provided between the first and second estimators (302, 303) so that output from the first estimator is used as input to the second estimator and vice versa, the method comprising the steps of: - obtaining operational data of the energy storage system by collecting measurement data relating to operating conditions of the energy storage system, - feeding the obtained operational data to the first and the second estimators (302, 303), respectively, - using the first estimator, estimating the at least one battery state based on at least the obtained operational data and output from the second estimator, - using the second estimator, estimating changes around the nominal values of the set of battery parameters based on at least the obtained operational data and output from the first estimator, - adaptively adjusting the nominal values of the set of battery parameters to account for slow timescale variations arising due to ageing of the at least one battery unit, wherein the method is characterised by: - adaptively adjusting at least one of the first and the second tuning parameters to account for fast timescale variations of the at least one battery state and/or the set of battery parameters arising due to varying operating conditions of the energy storage system. - a first estimator comprising a first non-linear observer, the first estimator being configured to estimate at least one battery state of the energy storage system using a prediction model, the first estimator having first tuning parameters, - a second estimator comprising at least one second non-linear observer, the second estimator being configured to track changes around nominal values of a set of battery parameters of the energy storage system, the second estimator having second tuning parameters, a first feedback loop being provided between the first and second estimators (302, 303) so that output from the first estimator is used as input to the second estimator and vice versa, - obtaining operational data of the energy storage system by collecting measurement data relating to operating conditions of the energy storage system, - feeding the obtained operational data to the first and the second estimators (302, 303), respectively, - using the first estimator, estimating the at least one battery state based on at least the obtained operational data and output from the second estimator, - using the second estimator, estimating changes around the nominal values of the set of battery parameters based on at least the obtained operational data and output from the first estimator, - adaptively adjusting the nominal values of the set of battery parameters to account for slow timescale variations arising due to ageing of the at least one battery unit, wherein the method is characterised by: - adaptively adjusting at least one of the first and the second tuning parameters to account for fast timescale variations of the at least one battery state and/or the set of battery parameters arising due to varying operating conditions of the energy storage system. - adaptively adjusting at least one of the first and the second tuning parameters to account for fast timescale variations of the at least one battery state and/or the set of battery parameters arising due to varying operating conditions of the energy storage system.