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Technical Paper

Energy Management Based on D4QN Reinforcement Learning for a Series-Parallel Multi-Speed Hybrid Electric Vehicle

2023-10-30
2023-01-7007
Reinforcement learning is a promising approach to solve the energy management for hybrid electric vehicles. In this paper, based on the DQN (Deep Q-Network) reinforcement learning algorithm which is widely used at present, double DQN, dueling DQN and learning from demonstration are integrated; states, actions, rewards and the experience pool based on the characteristics of series-parallel multi-speed hybrid powertrain are designed; the hybrid energy management strategy based on D4QN (Double Dueling Deep Q-Network with Demonstrations) algorithm is established. Based on the training results of D4QN algorithm, multi-parameter analysis under state and action space, HCU (Hybrid control unit) application and MIL (Model in-loop) test research are conducted.
Journal Article

Performance Optimization Using ANN-SA Approach for VVA System in Diesel Engine

2022-03-29
2022-01-0628
Diesel engine is vital in the industry for its characteristics of low fuel consumption, high-torque, reliability, and durability. Existing diesel engine technology has reached the upper limit. It is difficult to break through the fuel consumption and emission of diesel engines. VVA (Variable Valve Actuation) is a new technology in the field of the diesel engines. In this paper, GT-Suite and ANN (artificial neural network) model are established based on engine experimental data and DoE simulation results. By inputting Intake Valve Opening crake angle (IVO), Intake Valve Angle Multiplier (IVAM) and Exhaust Valve Angle Multiplier (EVAM) into the ANN Model, and by using SA (simulated annealing algorithm), the optimized results of intake and exhaust valve lift under the target conditions are obtained.
Technical Paper

Research on Control Algorithm of Air Supply System for High-Pressure PEMFC Engine

2019-04-02
2019-01-0379
The Proton Exchange Membrane Fuel Cell (PEMFC) is the most widely used engine in fuel cell vehicles. For PEMFC, whether the supply of oxygen for cathode is adequate or not is a critical factor for its net output power and service life, and the proper control of air supply mass flow and pressure can effectively improve its system performance and efficiency. At present, fuel cells need to reduce the mass and volume and increase the power density. Therefore, it is necessary to increase the air supply pressure for PEMFC. But at the same time, many auxiliary devices are appended to the system to provide high-pressure air, such as air compressor, intercooler, and back pressure valve, which make the control of the entire air supply system very complicated. So an excellent control algorithm is needed.
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