Sponge Supercapacitor rule-based energy management strategy for wireless sensor nodes optimized by using dynamic programing algorithm

Energy ◽  
2021 ◽  
pp. 122368
Author(s):  
Xinzhi Liu ◽  
Nanjian Qi ◽  
Keren Dai ◽  
Yajiang Yin ◽  
Jiahao Zhao ◽  
...  
Keyword(s):  
Energy Management ◽  
Management Strategy ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Energy Management Strategy ◽  
Wireless Sensor Nodes ◽  
Rule Based ◽  
Dynamic Programing

scholarly journals An Adaptive Energy Management Strategy to Extend Battery Lifetime of Solar Powered Wireless Sensor Nodes

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 88289-88300 ◽  
Author(s):  
Nanjian Qi ◽  
Keren Dai ◽  
Fang Yi ◽  
Xiaofeng Wang ◽  
Zheng You ◽  
...  
Keyword(s):  
Energy Management ◽  
Management Strategy ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Energy Management Strategy ◽  
Wireless Sensor Nodes ◽  
Battery Lifetime ◽  
Solar Powered

A novel hybrid energy management strategy of a diesel-electric hybrid ship based on dynamic programing and model predictive control

2022 ◽  
pp. 147509022110689
Author(s):  
Yupeng Yuan ◽  
Mingshuang Chen ◽  
Jixiang Wang ◽  
Wanneng Yu ◽  
Boyang Shen
Keyword(s):  
Model Predictive Control ◽  
Energy Management ◽  
Predictive Control ◽  
Control Strategy ◽  
Management Strategy ◽  
Energy Management Strategy ◽  
Threshold Control ◽  
Rule Based ◽  
Dynamic Programing ◽  
Simulation Results

The energy-saving characteristics of diesel-electric series hybrid ships largely depend on their energy management strategy. In this paper, a strategy that combines dynamic programing and model predictive control (DP-MPC) is proposed to solve the energy management problems of diesel-electric hybrid ships. The DP-MPC strategy has considered some typical working conditions of a ship, and the corresponding influence of white noise disturbance on the control strategy was studied. The simulation results show that the DP-MPC strategy has an excellent anti-interference capability. The control performance of the DP-MPC strategy is then further analyzed and compared with the rule-based logic threshold control strategy. The simulation results show that the proposed DP-MPC strategy can save 2.5% of the fuel consumption and has a better anti-interference capability than the rule-based control strategy.

scholarly journals Adaptive Rule-Based Energy Management Strategy for a Parallel HEV

Energies ◽  
2019 ◽  
Vol 12 (23) ◽  
pp. 4472 ◽  
Author(s):  
Rishikesh Mahesh Bagwe ◽  
Andy Byerly ◽  
Euzeli Cipriano dos Santos ◽  
Ben-Miled
Keyword(s):  
Fuel Consumption ◽  
Energy Management ◽  
Duty Cycle ◽  
Management Strategy ◽  
Hybrid Electric Vehicle ◽  
Detailed Knowledge ◽  
Energy Management Strategy ◽  
Rule Based ◽  
Engine Efficiency ◽  
Efficiency Map

This paper proposes an Adaptive Rule-Based Energy Management Strategy (ARBS EMS) for a parallel hybrid electric vehicle (HEV). The aim of the strategy is to facilitate the aftermarket hybridization of medium- and heavy-duty vehicles. ARBS can be deployed online to optimize fuel consumption without any detailed knowledge of the engine efficiency map of the vehicle or the entire duty cycle. The proposed strategy improves upon the established Preliminary Rule-Based Strategy (PRBS), which has been adopted in commercial vehicles, by dynamically adjusting the regions of operations of the engine and the motor. It prevents the engine from operating in highly inefficient regions while reducing the total equivalent fuel consumption of the vehicle. Using an HEV model developed in Simulink®, both the proposed ARBS and the established PRBS strategies are compared over an extended duty cycle consisting of both urban and highway segments. The results show that ARBS can achieve high MPGe with different thresholds for the boundary between the motor region and the engine region. In contrast, PRBS can achieve high MPGe only if this boundary is carefully established from the engine efficiency map. This difference between the two strategies makes the ARBS particularly suitable for aftermarket hybridization where full knowledge of the engine efficiency map may not be available.

scholarly journals Optimization of Energy Management Strategy for the EPS with Hybrid Power Supply Based on PSO Algorithm

Energies ◽  
2020 ◽  
Vol 13 (2) ◽  
pp. 428
Author(s):  
Bin Tang ◽  
Di Zhang ◽  
Haobin Jiang ◽  
Yinqiu Huang
Keyword(s):  
Energy Management ◽  
Power Supply ◽  
Power Distribution ◽  
Management Strategy ◽  
Pso Algorithm ◽  
Output Current ◽  
Energy Management Strategy ◽  
Power Requirement ◽  
Rule Based ◽  
Hybrid Power

The traditional vehicle power supply is unable to meet the power requirement of electric power steering system (EPS) in heavy-duty vehicles at low speeds. A novel EPS with hybrid power supply (HP-EPS) is constructed in this paper, and a new optimized rule-based energy management strategy of hybrid power supply system is designed. The strategy determines the power distribution of the vehicle power supply (VPS) and super capacitor (SC), as well as the charging or discharging of SC. Furthermore, to minimize the output current fluctuation of the VPS, the optimization model of parameters in the strategy is established and the particle swarm optimization algorithm (PSO) algorithm is applied to optimize the rules in the energy management strategy. The verification for the designed energy management strategy is carried out in MATLAB/Simulink and results show that the output current peak of VPS decreases by 33% and its fluctuation depresses significantly. In addition, the SC is charged timely and fast, which is beneficial to guarantee enough state of charge (SOC) of SC. In conclusion, the optimized rule-based energy management strategy used for the HP-EPS system can meet the current requirement of EPS and effectively reduce the peak and fluctuation of the VPS output current.

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