On January 8, the 2018 National Science and Technology Awards Conference was held in Beijing, and the highest award on behalf of the national science and technology work was officially released. A total of 278 projects and 7 scientific and technological experts won awards, including 38 national science awards, 67 national technology invention awards, 173 national science and technology progress awards, and five people from the People's Republic of China International Science and Technology Cooperation Award. Winners of the highest science and technology award are Academician Liu Yongtan, an expert in radar technology and signal processing, and Academician Qian Qihu, an expert in military engineering.
In the field of lithium batteries, the key technology of lithium iron phosphate power battery manufacturing and its application process completed by the team of Professor Ma Zifeng from the School of Chemistry and Chemical Engineering of Shanghai Jiaotong University won the "Second Prize of the National Science and Technology Progress Award 2018".
The main finishers of this project include Ma Zifeng, Liao Xiaozhen, Zhang Zifeng, Zhao Zhengwei, Ding Jianmin, He Yijun, Yang Jun, Yin Shaowen, He Yushi, Shen Jiani, etc. The completion units are Shanghai Jiaotong University, BYD Automotive Industry Co., Ltd., and Shanghai Zhongju Jiahua Battery Technology Co., Ltd Company and Jiangsu Leneng Battery Co., Ltd.
The lithium iron phosphate (LifFePO4) power battery has the advantages of good safety, long cycle life, and high cost performance. This project addresses the problems of low conductivity, low rate performance and low temperature performance of lithium iron phosphate, and has pioneered a new reaction for the synthesis of elemental iron atom economic lithium iron phosphate. Established several 10,000-ton nanometer lithium iron phosphate material production lines. Developed a new manufacturing process for lithium iron phosphate power battery, which increased its energy density to above 175Wh / kg, and established accurate prediction models for the state of charge (SOC) and state of health (SOH) of lithium batteries. The results are applied to BYD, Huawei, China Poly Battery and China Southern Power Grid, and their products are sold at home and abroad.