Flexible path planning-based reconfiguration strategy for maximum capacity utilization of battery pack

Maximizing the utilization of lithium-ion battery capacity is an important means to alleviate the range anxiety of electric vehicles.Battery pack inconsistency is the main limiting factor for improving battery pack capacity utilization,and poses major safety hazards to energy storage systems.To solve this problem,a maximum capacity utilization scheme based on a path planning algorithm is proposed.Specifically,the reconfigurable topology proposed is highly flexible and fault-tolerant,enabling battery pack consistency through alternating cell discharge and reducing the increased risk of short circuits due to relay error.The Dijkstra algorithm is used to find the optimal energy path,which can effectively remove faulty cells and find the current path with the best consistency of the battery pack and the lowest relay loss.Finally,the effectiveness of the scheme is verified by hardware-in-the-loop experiments,and the experimental results show that the state-of-charge SOC consistency of the battery pack at the end of discharge is increased by 34.18%,the relay energy loss is reduced by 0.16%,and the fault unit is effectively isolated.

Investigating the Impact of Capacity Utilization on Carbon Dioxide Emission: Evidence from China's Iron and Steel Industry

In recent years, China’s industrialization and urbanization have deepened, and the economy has grown considerably. But at the same time, they have also brought about many environmental problems. As a pillar of the national economy, the iron and steel(IS) industry is one of the most emitting and energy-consuming sub-sectors of the industrial sector. It is also one of the industries with the most severe overcapacity problem in China. In this paper, we explore the impact of capacity utilization on carbon dioxide emission based on panel data of China’s iron and steel industry from 2005 to 2014. We also tested the heterogeneity in different regions and different sub-samples. Results show that capacity utilization and carbon dioxide emission are positively correlated. However, the impact of capacity utilization on carbon dioxide emission differs when considering regional heterogeneity. Results in all three regions show a positive relationship between capacity utilization and carbon dioxide emission,but the impact intensity is strongest in the western region, followed by the eastern and central regions.Moreover, capacity utilization impacts carbon dioxide emission by influencing firm numbers in the iron and steel industry and energy consumption. Further analysis shows that there exists a threshold effect in different stages of energy consumption and energy structure. Finally, some findings and practical policy recommendations are provided.

Does Over-credit Stimulate Corporate Investment？ Evidence from Listed Companies in China

We define and quantify for the first time over-credit at the firm level, which refers to the case in which the amount of bank credit that a firm obtains exceeds its expenditure on corporate investment for the year. Then, we explore how over-credit affects corporate investment to determine whether credit expansion in China is consistent with the principle of finance serving the real economy. The results show that over-credit promotes firm investment, and this effect was enhanced by the housing boom. However, the effect of the property market reversed after 2012, owing to China＇s economic transition from a quantitative to a structural mismatch between supply and demand. Finally, we explore how over-credit affects the capacity utilization ratio and whether it has aggravated the overcapacity problem in China. The results show that over-credit reduces firms＇ capacity utilization ratio. This finding indicates that excessive credit expansion has exacerbated the overcapacity problem in China.

State of health based battery reconfiguration for improved energy efficiency

This paper analyzes the system-level state of health(SOH)and its dependence on the SOHs of its component battery modules.Due to stochastic natures of battery aging processes and their dependence on charge/discharge rate and depth,operating temperature,and environment conditions,capacities of battery modules decay unevenly and randomly.Based on estimated SOHs of battery modules during battery operation,we analyze how the SOH of the entire system deteriorates when battery modules age and become increasingly diverse in their capacities.A rigorous mathematical analysis of system-level capacity utilization is conducted.It is shown that for large battery strings with uniformly distributed capacities,the average string capacity approaches the minimum,implying an asymptotically near worst-case capacity utility without reorganization.It is demonstrated that the overall battery usable capacities can be more efficiently utilized to achieve extended operational ranges by using battery reconfiguration.An optimal regrouping algorithm is introduced.Analysis methods,simulation examples,and a case study using real-world battery data are presented.