Forecast Research into Demand of Automotive Storage Battery Based on Gray-Markov Chain Model-The Case of Demand Prediction of Sail Company in the Northern Region of China

The accurate demand prediction of storage battery is crucial for the logistics research, such as establishing an efficient storage battery DC, determining the appropriate after-sales maintenance center and so forth. Setting the automotive storage battery as the research object and combining with the demand randomness, the paper proposed a demand prediction method of automotive storage battery based on gray-Markov chain model. Primarily, the paper applied gray system model to predict the overall trend of timing variation of the system. And then it used Markov chain model to correct the residuals and relative error of the forecast value to predict the range of random fluctuations. The analysis of the actual case showed that this prediction method can predict the demand of automotive storage battery better.