Research on fault detection and diagnosis of automatic transmission control system under steady state condition

Fault detection and diagnosis of automatic transmission control system (ASCS) is realized by multi-way principal component analysis (MPCA). According to fault diagnosis of ASCS under steady state condition, firstly, the state variable characteristics under steady state condition are analyzed and the feasibility of MPCA algorithm is researched by taking ASCS's control cycle characteristics as the basis. Secondly, ASCS's multi-way principal component models are established by faultless historical data. And the comprehensive monitoring indicator, OIndex, is used for process fault detection. When a fault occurs, a fault isolation is achieved by establishing a mapping relationship among the comprehensive monitoring indicator, score vectors and state variable characteristics. At last, the vehicle test and simulation test are used to prove the effectiveness and real-time of MPCA algorithm under ASCS's steady state condition.