以电动汽车电池组，航天探测器，多旋翼无人机为代表的储能、动力和负载等关键设备均属于平衡系统，针对平衡系统的重要性，以及平衡系统可靠性研究成果较少，传统的系统可靠性建模和分析理论对平衡系统的独特性考虑不足的现实，本课题将在深入调研的基础上，首先，以平衡的概念为切入点，依据平衡系统组成结构、运行机制、失效准则、运行环境等要素，构建平衡系统可靠性模型；其次，综合应用有限马尔可夫链嵌入法，马尔可夫过程嵌入法，通用生成函数法，分析平衡系统可靠度及相关概率指标；最后，针对平衡系统所具有的独特性质，综合考虑可靠性和成本等因素，构建系统设计优化模型，维修策略优化模型，以及联合优化模型，并提出求解算法。.本项目研究成果可直接应用于航空航天、军事武器、新能源等领域的储能、动力和负载等设备的优化设计和运维策略的制定。此外，本项目研究还将丰富系统可靠性模型理论，推动有限马尔可夫链嵌入法和马尔可夫过程嵌入法的发展。

Balanced systems have wide applications on the key equipment, with battery packs in electric vehicles, space probes and unmanned aerial vehicles with multiple rotors as the representatives in the fields of storage, power and load respectively. The great importance of balanced systems has been increasingly realized, however, the existing research on reliability of balanced systems is rather few and the peculiar characteristic of balanced systems was insufficiently considered in the traditional theory of system reliability modelling and analysis. Faced with the above research status of balanced systems, this project intends to conduct the following three aspects of research based on a thorough investigation: firstly, taking balance concepts as the breakthrough point, various reliability models of balanced systems can be constructed by considering diverse system structures, operation mechanisms, failure criteria, operation environments and so on; Secondly, the reliability and related probabilistic indices of balanced systems can be derived by integrated use of finite Markov chain imbedding approach, Markov process imbedding method and universal generating function; Finally, according to the peculiar characteristic of balanced systems, optimization models of system design, maintenance policy as well as related joint optimization models can be established and the corresponding solving algorithms can be proposed in overall consideration of the system reliability and cost..The research results of this project can be applied directly in the optimization design and maintenance strategy for the storage, power and load equipment in the fields of aerospace, military weapon and new energy. Furthermore, it is expected that this project will enrich the theory of system reliability modelling and promote the developments of finite Markov chain imbedding approach and Markov process imbedding method.