Abstract: An uncertain noisy filtering-based fault diagnosis method for a power battery management system is described. The method includes establishing an electro-thermal coupling model of the power battery system; extending an output vector of the system according to a state constraint of a power battery, and expanding a state vector of the system according to a fault of the power battery system to obtain an augmented system of the power battery system; obtaining an estimation interval of a power battery sensor fault by using a zonotope Kalman filtering method; judging whether the power battery management system has a fault according to upper and lower bounds of fault estimation; if a fault occurs, determining a fault type and a fault time according to a result.

Abstract: Disclosed is a state estimation method for a power battery formation process based on convex space filtering, belonging to the technical field of power battery manufacturing. The method performs state estimation on a time delay system by a filtering method, and an iterative replacement method is provided for converting the state quantity at a time k to the state quantity at a time k?h and subsequent items, so as to combine time delay items, thereby avoiding the problem that the dimension is increased when a state matrix A and a state matrix Ah of a time-delay state quantity are subsequently combined into a new state matrix, and reducing the computation complexity and computation time in subsequent computations. Moreover, the estimation accuracy is also improved to a certain extent because of the cancellation of the same items in the iterative replacement.

Abstract: Disclosed is a state estimation method for a power battery formation process based on convex space filtering, belonging to the technical field of power battery manufacturing. The method performs state estimation on a time delay system by a filtering method, and an iterative replacement method is provided for converting the state quantity at a time k to the state quantity at a time k?h and subsequent items, so as to combine time delay items, thereby avoiding the problem that the dimension is increased when a state matrix A and a state matrix Ah of a time-delay state quantity are subsequently combined into a new state matrix, and reducing the computation complexity and computation time in subsequent computations. Moreover, the estimation accuracy is also improved to a certain extent because of the cancellation of the same items in the iterative replacement.

Abstract: The present disclosure discloses an uncertain noisy filtering-based fault diagnosis method for a power battery management system and belongs to the field of power battery fault diagnosis. The method comprises: establishing an electro-thermal coupling model of a power battery system; extending an output vector of the system according to a state constraint of a power battery, and expanding a state vector of the system according to a fault of the power battery system to obtain an augmented system of the power battery system; obtaining an estimation interval of a power battery sensor fault by using a zonotope Kalman filtering method; judging whether the power battery management system has a fault according to upper and lower bounds of fault estimation, and if a fault occurs, determining a fault type and a fault time according to a result.