Method for calibrating a system comprising a plurality of sensors , wherein each of the sensors is arranged on an element of a vehicle , namely on an axle of the vehicle and/or a wheel or a suspension system of the vehicle , the method comprising: carrying out a first number of measurements of an axle load or wheel load when the unladen vehicle is at a standstill using each of the plurality of sensors ; carrying out a first number of measurements of an axle load or wheel load when the laden vehicle is at a standstill using each of the plurality of sensors , wherein each of the measurements is carried out in each case under the influence of disturbance variables identical to those of one of the measurements carried out for the unladen vehicle ; carrying out a plurality of measurements of an axle load or wheel load at regular intervals while the laden vehicle is travelling using each of the plurality of sensors ; determining at least one disturbance variable at regular intervals while the laden vehicle is travelling; and creating an algorithm that takes into account the measured values determined when the unladen vehicle is at a standstill, the measured values determined when the laden vehicle is at a standstill, the measured values determined while the laden vehicle is travelling, and the disturbance variables when the vehicle is at a standstill and while the vehicle is travelling, wherein the disturbance variables include an ambient temperature, the method being characterized in that , on the basis of this algorithm, measured values obtained as a result of a continuous weight measurement can be adapted to changing ambient conditions, namely a changed ambient temperature, during operation of the vehicle , and in that the algorithm is a self-learning algorithm, such that the data obtained in each case as a result of the continuous measurement are compared with a stored model for temperature calibration, as a result of which ageing-related changes to the axle , the suspension or the wheel are identified. carrying out a first number of measurements of an axle load or wheel load when the unladen vehicle is at a standstill using each of the plurality of sensors ; carrying out a first number of measurements of an axle load or wheel load when the laden vehicle is at a standstill using each of the plurality of sensors , wherein each of the measurements is carried out in each case under the influence of disturbance variables identical to those of one of the measurements carried out for the unladen vehicle ; carrying out a plurality of measurements of an axle load or wheel load at regular intervals while the laden vehicle is travelling using each of the plurality of sensors ; determining at least one disturbance variable at regular intervals while the laden vehicle is travelling; and creating an algorithm that takes into account the measured values determined when the unladen vehicle is at a standstill, the measured values determined when the laden vehicle is at a standstill, the measured values determined while the laden vehicle is travelling, and the disturbance variables when the vehicle is at a standstill and while the vehicle is travelling, wherein the disturbance variables include an ambient temperature, the method being characterized in that , on the basis of this algorithm, measured values obtained as a result of a continuous weight measurement can be adapted to changing ambient conditions, namely a changed ambient temperature, during operation of the vehicle , and in that the algorithm is a self-learning algorithm, such that the data obtained in each case as a result of the continuous measurement are compared with a stored model for temperature calibration, as a result of which ageing-related changes to the axle , the suspension or the wheel are identified. <EOS>