EV储能飞轮优化设计方法与结构研究
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摘要
为提高电动汽车飞轮辅助储能系统的能量回收率,对其能量储存的关键部件储能飞轮的结构进行优化设计。采用改进型差分进化算法,通过Matlab联合Ansys有限元分析软件,在安全系数为2的条件下,对储能飞轮结构进行优化设计。经过算法优化得到质量储能密度最大的储能飞轮结构,在算法优化的储能飞轮基础上,为增加有效回转半径,对储能飞轮轮辐进行结构设计,最终通过强度校核,得到采用轮辐结构可明显提高质量储能密度,但轮辐的数量对提高质量储能密度影响不大。采用改进型差分进化算法和轮辐结构联合优化设计储能飞轮,能够有效提高储能飞轮的质量储能密度,为设计储能飞轮的结构提供一种新思路。
In order to improve the energy recovery rate of the electric vehicle flywheel auxiliary energy storage system,the structure of the flywheel of the key component of energy storage is optimized. Under the condition of safety factor of 2,the improved differential evolution algorithm is used to optimize the design of the flywheel structure by Matlab combined with Ansys finite element analysis software. The flywheel structure with the highest energy storage density is obtained through algorithm optimization. Based on the algorithm-optimized flywheel,the spoke structure is designed to improve the radius of gyration. Finally,through the strength check,it can be concluded that the spokes structure can obviously improve the mass energy storage density,but the number of spokes has little effect on improving the mass energy storage density. The research shows that the improved differential evolution algorithm and the spoke structure jointly optimize the design of the flywheel,which can effectively improve the energy storage density of the flywheel,and provide a new idea for designing the structure of the flywheel.
In order to improve the energy recovery rate of the electric vehicle flywheel auxiliary energy storage system,the structure of the flywheel of the key component of energy storage is optimized. Under the condition of safety factor of 2,the improved differential evolution algorithm is used to optimize the design of the flywheel structure by Matlab combined with Ansys finite element analysis software. The flywheel structure with the highest energy storage density is obtained through algorithm optimization. Based on the algorithm-optimized flywheel,the spoke structure is designed to improve the radius of gyration. Finally,through the strength check,it can be concluded that the spokes structure can obviously improve the mass energy storage density,but the number of spokes has little effect on improving the mass energy storage density. The research shows that the improved differential evolution algorithm and the spoke structure jointly optimize the design of the flywheel,which can effectively improve the energy storage density of the flywheel,and provide a new idea for designing the structure of the flywheel.
引文
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[10]赵志伟,杨景明,呼子宇,等.基于一次指数平滑法的自适应差分进化算法[J].控制与决策,2016,31(5):790-796.ZHAO Z W,YANG J M,HU Z Y,et al. Self-adaptive differential evolution algorithm based on exponential smoothing[J]. Control and Decision,2016,31(5):790-796.
[11]李响,贾志伟.基于DE算法的10 kV网架结构多目标规划[J].中国电机工程学报,2018,38(S1):99-104.LI X,JIA Z W. Multi-objective programming of the 10 k V network structure based on DE algorithm[J]. Proceedings of the CSEE,2018,38(S1):99-104.
[12]侯莹,韩红桂,乔俊飞.基于参数动态调整的多目标差分进化算法[J].控制与决策,2017,32(11):1985-1990.HOU Y,HAN H G,QIAO J F. Adaptive multi-objective differential evolution algorithm based on the dynamic parameters adjustment[J]. Control and Decision,2017,32(11):1985-1990.
[13]王强,赵永翔,王欢.铁路D1车轮钢的疲劳可靠性寿命与强度的试验及表征[J].机械工程学报,2014,50(14):50-55.WANG Q,ZHAO Y X,WANG H. Experiments and characterization on the probabilistic fatigue lives and strengths of D1 railway wheel steel[J]. Journal of Mechanical Engineering,2014,50(14):50-55.
[14]张志远,刘玉梅,姚为民,等.基于实测的车轮虚拟试验台搭建及参数修正[J].东北大学学报(自然科学版),2017,38(6):845-848.ZHANG Z Y,LIU Y M,YAO W M,et al. Construction and parameters correction of wheel virtual test bench based on measurement[J]. Journal of Northeastern University(Natural Science),2017,38(6):845-848.
[15]毕征,单颖春,刘献栋.车轮在动态弯曲载荷作用下的应力分析[J].汽车工程,2014,36(9):1112-1116.BI Z,SHAN Y C,LIU X D. Stress analysis of wheels subjected to dynamic bending loads[J]. Automotive Engineering,2014,36(9):1112-1116.
[2]金光宇,陈劭,徐向波.车载磁悬浮飞轮电池动力学分析及悬浮研究[J].林业机械与木工设备,2018,46(4):23-28.JIN G Y,CHEN Z,XU X B. Dynamic analysis and static suspension research on vehicle-mounted magnetic suspension flywheel batteries[J]. Forestry Machinery&Woodworking Equipment,2018,46(4):23-28.
[3]李振宇,黄格省,黄晟.推动我国能源消费革命的途径分析[J].化工进展,2016,35(1):1-9.LI Z Y,HUANG G S,HUANG S. Analysis on ways to promote energy consumption revolution in China[J]. Chemical Industry and Engineering Progress,2016,35(1):1-9.
[4]李建林,马会萌,惠东.储能技术融合分布式可再生能源的现状及发展趋势[J].电工技术学报,2016,31(15):1-10.LI J L,MA H M,HUI D. Present development condition and trends of energy storage technology in the integration of distributed renewable energy[J]. Transactions of China Electrotechnical Society,2016,31(15):1-10.
[5]张新宾,储江伟,李洪亮,等.飞轮储能系统关键技术及其研究现状[J].储能科学与技术,2015,12(1):55-60.ZHANG X B,CHU J W,LI H L,et al. Key technologies of flywheel energy storage systems and current development status[J].Energy Storage Science and Technology,2015,12(1):55-60.
[6]黄菊花,王傅忠,杨军平.飞轮式汽车制动能量回收系统的研究[J].系统仿真学报,2016,28(5):1197-1205.HUANG J H,WANG F Z,YANG J P. Study on flywheel automotive-brake energy recovery system[J]. Journal of System Simulation,2016,28(5):1197-1205.
[7]袁绍军,白雪松,潘立巍,等.微电网用飞轮储能支承系统多目标控制[J].电工技术学报,2015,30(S1):406-411.YUAN S J,BAI X S,PAN L W,et al. A multi-objective control algorithm for micro grid with flywheel energy storage supporting system[J]. Transactions of China Electro technical Society,2015,30(S1):406-411.
[8]戴兴建,姜新建,王秋楠,等. 1 MW/60 MJ飞轮储能系统设计与实验研究[J].电工技术学报,2017,32(21):169-175.DAI X J,JIANG X J,WANG Q N,et al. The design and testing of a 1 MW/60 MJ flywheel energy storage power system[J]. Transactions of China Electrotechnical Society,2017,32(21):169-175.
[9]王喆,谭天力,周双,等.基于粒子群算法的磁悬浮储能飞轮结构优化设计[J].机械工程与自动化,2013,12(6):7-9.WANG Z,TAN T L,ZHOU S,et al. Optimization design of magnetic levitation energy storage flywheel based on particle swarm optimization[J]. Mechanical Engineering&Automation,2013,12(6):7-9.
[10]赵志伟,杨景明,呼子宇,等.基于一次指数平滑法的自适应差分进化算法[J].控制与决策,2016,31(5):790-796.ZHAO Z W,YANG J M,HU Z Y,et al. Self-adaptive differential evolution algorithm based on exponential smoothing[J]. Control and Decision,2016,31(5):790-796.
[11]李响,贾志伟.基于DE算法的10 kV网架结构多目标规划[J].中国电机工程学报,2018,38(S1):99-104.LI X,JIA Z W. Multi-objective programming of the 10 k V network structure based on DE algorithm[J]. Proceedings of the CSEE,2018,38(S1):99-104.
[12]侯莹,韩红桂,乔俊飞.基于参数动态调整的多目标差分进化算法[J].控制与决策,2017,32(11):1985-1990.HOU Y,HAN H G,QIAO J F. Adaptive multi-objective differential evolution algorithm based on the dynamic parameters adjustment[J]. Control and Decision,2017,32(11):1985-1990.
[13]王强,赵永翔,王欢.铁路D1车轮钢的疲劳可靠性寿命与强度的试验及表征[J].机械工程学报,2014,50(14):50-55.WANG Q,ZHAO Y X,WANG H. Experiments and characterization on the probabilistic fatigue lives and strengths of D1 railway wheel steel[J]. Journal of Mechanical Engineering,2014,50(14):50-55.
[14]张志远,刘玉梅,姚为民,等.基于实测的车轮虚拟试验台搭建及参数修正[J].东北大学学报(自然科学版),2017,38(6):845-848.ZHANG Z Y,LIU Y M,YAO W M,et al. Construction and parameters correction of wheel virtual test bench based on measurement[J]. Journal of Northeastern University(Natural Science),2017,38(6):845-848.
[15]毕征,单颖春,刘献栋.车轮在动态弯曲载荷作用下的应力分析[J].汽车工程,2014,36(9):1112-1116.BI Z,SHAN Y C,LIU X D. Stress analysis of wheels subjected to dynamic bending loads[J]. Automotive Engineering,2014,36(9):1112-1116.
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