Battery management is the key technical link for electric vehicles. A good battery management system can realize the balanced charge and discharge of batteries, reducing the capacity degradation and the loss of health caused by battery overcharge and discharge, which all depend on the real-time and accurate estimation of the battery’s state of charge (SOC). However, the battery’s SOC has highly complex nonlinear time-varying characteristics related to the complex chemical and physical state and dynamic environmental conditions, which are difficult to measure directly, and this has become a difficulty in design and research. According to the characteristics of ternary lithium-ion batteries of electric vehicles, a battery SOC dual estimation algorithm based on the Variable Forgetting Factor Recursive Least Square (VFFRLS) and Multi-Innovation Unscented Kalman Filter (MIUKF) is proposed in this paper. The VFFRLS algorithm is used to estimate battery model parameters, and the MIUKF algorithm is used to estimate the battery’s SOC in real time. The two algorithms are coupled to update battery model parameters and estimate the SOC. The experiment results show that the algorithm has high accuracy and stability.

Automation equipment with different functions from different manufacturers is common in lithium ion battery manufacturing workshops, which is manifested as heterogeneous data distributed at different network levels at the information level. The interconnection between a workshop system and equipment is the basis for realizing manufacturing informatization and intelligence, and is a core problem of intelligent manufacturing workshop integration. The key to solve this problem is to establish a standardized and consistent information model. Aiming at the problem of information interconnection, this paper established an information model of the intelligent manufacturing workshop of lithium ion batteries based on the analysis of the architecture, functional categories, and information interaction of the intelligent manufacturing workshop. Then, by clarifying the attribute set, component set, and the information objects contained in each information model, the hierarchical architecture of the information model was constructed. Then, the rules that map the information model in to the OLE for Process Control Unified Architecture (OPC UA) address space is established. The approach for implementing data storage and interaction of the information model based on the OPC UA server/client are also discussed. Finally, taking the soft-pack battery manufacturing workshop as an example, the information model is applied to realize the interconnection and interoperability of production management data, material management data, equipment management data, and quality management data among various levels of the workshop, which verifies the feasibility of the proposed information model.

In order to promote the development of logistics IT construction for national modern trade and exhibition parks, the integrated business of trade logistics is taken as the objective. Firstly, the service mode and business process of the information platform are analyzed, and then, the functional structure and system architecture of the platform are studied. Finally, the key problems of information platform construction for modern trade and exhibition logistics parks are deeply discussed so as to propose an information platform construction program for modern trade and exhibition logistics parks.

The authors wish to make the following corrections in Section 3