Abstract: A method and system for control of BTM of electric drive bulldozers based on deep learning includes: obtaining a micro-load segment at the current moment in a load spectrum and predicting a micro-load segment at the next moment using a Markov chain model; carrying out a weighting calculation of the segment using the segment at the current moment and a corresponding weight thereof with the predicted segment and a corresponding weight thereof, and then calculating motor speed, motor torque, and a state of charge (SOC) of battery under the segment after being weighted; and taking a real-time battery outlet water temperature, occupant cabin temperature, occupant cabin target temperature and ambient temperature as well as the motor speed, motor torque and SOC, so as to obtain a control strategy of the electric compressor speed, and further obtain a method for control of BTM of the electric drive bulldozer.