The Design of APU(Auxiliary Power Unit) Control Strategy

2013 ◽  
Vol 724-725 ◽  
pp. 1440-1443
Author(s):  
Ling Shan Chen ◽  
Xiang Er Huang ◽  
Pin Gan ◽  
Wei Cheng
Keyword(s):  
Power Unit ◽  
Control Strategy ◽  
Pid Control ◽  
Control Algorithm ◽  
Bench Test ◽  
Control Torque ◽  
Auxiliary Power Unit ◽  
Power Simulation ◽  
Auxiliary Power ◽  
Entire Vehicle

APU(Auxiliary Power Unit) control strategy was designed by the target of actual output power following the demanded power and the fuel consumption minimum. The preset demanded power of the entire vehicle has been decoupling controlled, using PID control algorithm to control the speed of the engine and vector control algorithm to control torque of generator, to realize decoupling control of the demanded power. Simulation result and bench test verified control strategy and achieved the goal of vehicle fuel saving 20% by nine “NEDC” cycles.

scholarly journals Powering Mode-Integrated Energy Management Strategy for a Plug-In Hybrid Electric Truck with an Automatic Mechanical Transmission Based on Pontryagin’s Minimum Principle

2018 ◽  
Vol 10 (10) ◽  
pp. 3758 ◽  
Author(s):  
Shaobo Xie ◽  
Xiaosong Hu ◽  
Kun Lang ◽  
Shanwei Qi ◽  
Tong Liu
Keyword(s):  
Dynamic Programming ◽  
Power Unit ◽  
Energy Management ◽  
Control Strategy ◽  
Minimum Principle ◽  
Mechanical Transmission ◽  
Auxiliary Power Unit ◽  
Auxiliary Power ◽  
Pontryagin's Minimum Principle ◽  
Hybrid Electric

Pontryagin’s Minimum Principle (PMP) has a significant computational advantage over dynamic programming for energy management issues of hybrid electric vehicles. However, minimizing the total energy consumption for a plug-in hybrid electric vehicle based on PMP is not always a two-point boundary value problem (TPBVP), as the optimal solution of a powering mode will be either a pure-electric driving mode or a hybrid discharging mode, depending on the trip distance. In this paper, based on a plug-in hybrid electric truck (PHET) equipped with an automatic mechanical transmission (AMT), we propose an integrated control strategy to flexibly identify the optimal powering mode in accordance with different trip lengths, where an electric-only-mode decision module is incorporated into the TPBVP by judging the auxiliary power unit state and the final battery state-of-charge (SOC) level. For the hybrid mode, the PMP-based energy management problem is converted to a normal TPBVP and solved by using a shooting method. Moreover, the energy management for the plug-in hybrid electric truck with an AMT involves simultaneously optimizing the power distribution between the auxiliary power unit (APU) and the battery, as well as the gear-shifting choice. The simulation results with long- and short-distance scenarios indicate the flexibility of the PMP-based strategy. Furthermore, the proposed control strategy is compared with dynamic programming (DP) and a rule-based charge-depleting and charge-sustaining (CD-CS) strategy to evaluate its performance in terms of computational accuracy and time efficiency.

Optimization and realization on the coordination control strategy for auxiliary power unit of range-extended electric vehicle

2021 ◽  
pp. 095440702110669
Author(s):  
Hanwu Liu ◽  
Yulong Lei ◽  
Yao Fu ◽  
Xingzhong Li
Keyword(s):  
Control System ◽  
Control Strategy ◽  
Pid Control ◽  
Working Condition ◽  
Control Strategies ◽  
Control Model ◽  
Torque Control ◽  
Coordination Control ◽  
Auxiliary Power Unit ◽  
Auxiliary Power

The auxiliary power unit (APU) is a major power source of range-extended electric vehicle (R-EEV). Excellent coordination control strategy of APU has a great significance impact on improving the overall electrical control system performance of R-EEV. A coordination control strategy based on parameters adapt fuzzy-PID is proposed to ensure the dynamic and static response characteristics of the coordination control system. Firstly, the APU high precision simulation control model is built in GT-Power and Matlab-Simulink. Three coordination control strategies based on traditional PID control method are designed, namely, engine speed control model (ESCM), generator torque control model (GTCM), and APU speed-torque control model (AS-TCM). The three coordination control strategies are simulated on working conditions, which include start-up working condition, power raised working condition, and power reduced working condition. Combined with the PID control principle, the control performance and inherent limitations of three traditional PID control strategies (TPCS) are analyzed and compared. Then, according to the above simulation results of analysis and comparation, the parameters adapt fuzzy-PID control strategy (PAF-PCS) is designed and simulated. The results show that three control parameters ( kp, ki, kd) are changed in real time to ensure the flexibility and adaptability of the control system and improve the stability and robustness of control system. Finally, the results of bench test show that power responds quickly and no oscillation and fixed-point power generation works smoothly, which are basically consistent with the simulation results. Therefore, the PAF-PCS proposed in this paper has good feasibility and effectiveness.

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