A novel power state evaluation method for the lithium battery packs based on the improved external measurable parameter coupling model.

The power state evaluation plays a decisive influence on the safety implication of the lithium battery packs, and there is no effective online evaluation method so far due to the imbalance phenomenon among the internal connected battery cells, which cannot be abstained by the advancement of the materials and techniques. A novel power state mathematical evaluation method is proposed in this paper by investigating the improved external parameter coupling treatment, in which the mutual relationship description is conducted by the parameter information feature decomposition together with the Bayesian sequential decision algorithm. The complicated power state evaluation model with the coupling relationship decomposition is constructed by investigating the non-convex optimization treatment under complex working conditions for the lithium battery packs. The evidence combination is realized by introducing the information fusion strategy, according to which the multi criteria decision is realized by using the evidence theory. As can be seen from the experimental results, the voltage difference is within 10 mV in both of the first and the second phases, which increases rapidly in the third phase and reaches a maximum of 120 mV. Meanwhile, its power state evaluation accuracy is 95.00% and has a good output voltage tracking effect in the complex working conditions. The power state evaluation can be realized effectively by the proposed model constructing method, which is suitable for the complex battery cell combination structures and environmental influences, protecting the reliable and hierarchical working state monitoring and management of the lithium battery packs. It provides safety protection and energy management basis for the reliable power supply in the cleaner production of the power lithium battery packs

Control of active cell balancing systems : innovation report

Lithium-ion battery packs are increasingly being used for high power and energy applications such as electric vehicles and grid storage. These battery packs consist of many individual cells connected in series and/or parallel. Manufacturing tolerances and varied operating conditions mean that each cell will be different one from another, being able to store different amounts of energy and deliver different amounts of power. This also means some cells will finish charging or discharging before others, resulting in unutilised energy in the remaining cells. Passive balancing systems are often used in multi-cell battery packs to ensure that all of the cells can be fully charged. However, this does not account for differences in cell capacity, meaning that not all cells will be fully discharged. Active balancing systems have been developed to transfer energy between the cells, in theory allowing for stronger cells to compensate for weaker ones. However, their perceived cost and complexity have prevented them from being widely adopted in commercial applications. In this work, an innovative control strategy was developed to determine how and when to energy balance a set of battery cells, with the aim of maximising battery pack energy utilisation. A model-based control system was designed, using state of charge to evaluate the level of energy imbalance between cells. Real-time implementation using second-hand electric vehicle cells and commercial balancing hardware demonstrated that the control strategy can decrease the amount of unused charge in the battery pack from 8% with passive balancing to 1% with active balancing, which has significant impact for battery pack energy throughput, physical size, mass, and long-term health