Control Strategy for an Electromechanical Transmission Vehicle Based on a Double Markov Process

Based on an analysis of the driving demand and system dynamics of heavy-duty vehicles equipped with electromechanical transmission (EMT), a double Markov model is put forward to represent drivers' power demand for driving and electricity. Transfer probability matrices are calculated by utilizing the maximum likelihood estimation method. A power distribution control strategy based on stochastic dynamic programming (SDP) is proposed. With economy being the optimization goal, the model for power allocation control based on SDP is established while regarding the engine torque, motor speeds, vehicle speed and state of charge (SOC) as state variables' engine speed and motor torques as control variables' and power demands as interference variables. The SDP problem is solved by an improved policy iteration algorithm based on value iteration and policy iteration algorithms.

Automated summary

This study analyzes the driving demand and system dynamics of heavy-duty vehicles equipped with EMT, and proposes a double Markov model and a power distribution control strategy based on SDP. Transfer probability matrices are calculated using the maximum likelihood estimation method, and a model for power allocation control based on SDP is established.