Development of an Efficient Energy Management Strategy to Reduce Energy Consumption of Office Building Equipment

Author(s):  
Payal Soni ◽  
J. Subhashini
Vehicles ◽  
2021 ◽  
Vol 3 (3) ◽  
pp. 341-356
Author(s):  
Daizy Rajput ◽  
Jose M. Herreros ◽  
Mauro S. Innocente ◽  
Joschka Schaub ◽  
Arash M. Dizqah

Modern hybrid electric vehicles (HEVs) like the fourth generation of Toyota Prius incorporate multiple planetary gears (PG) to interconnect various power components. Previous studies reported that increasing the number of planetary gears from one to two reduces energy consumption. However, these studies did not compare one PG and two PGs topologies at their optimal operation. Moreover, the size of the powertrain components are not the same and hence the source of reduction in energy consumption is not clear. This paper investigates the effect of the number of planetary gears on energy consumption under optimal operation of the powertrain components. The powertrains with one and two PGs are considered and an optimal simultaneous torque distribution and mode selection strategy is proposed. The proposed energy management strategy (EMS) optimally distributes torque demands amongst the power components whilst also controlling clutches (i.e., mode selection). Results show that increasing from one to two PGs reduces energy consumption by 4%.


2021 ◽  
Vol 11 (2) ◽  
pp. 498
Author(s):  
Hao Wang ◽  
Hongwen He ◽  
Jianwei Li ◽  
Yunfei Bai ◽  
Yuhua Chang ◽  
...  

Electric sanitation vehicles have increasingly been applied to cleaning work due to the requirement of air pollution control. The power distribution and energy management strategy (EMS) influence the vehicle’s performance a lot both in the aspects of cleaning effect and electricity consumption. Aiming to improve energy economy and ensure clean tasks, first, the electricity consumption percentages of the vehicle onboard devices are analyzed and the main contributors are clarified, and the power requirement model of the working motor is built based on experimental data. Second, a universal modeling method of garbage distribution on the road surface is proposed, which implements a nonlinear autoregressive neural network as the predictor. Third, an adaptive model predictive control (AMPC)-based EMS is proposed and verified. The results show the AMPC method can accurately predict the garbage density and the proposed EMS can approximate the energy consumption of the DP-based EMS with little deviation. Compared to conventional rule-based EMS, the AMPC-based EMS achieved a 15.5% decrease in energy consumption as well as a 14.6% decrease in working time.


2019 ◽  
Vol 10 (2) ◽  
pp. 28
Author(s):  
Haiqing Wang ◽  
Hanfei Wu

This paper presents a real-time energy management strategy to distribute the power demand between two independent motors properly. Based on the characteristics of the novel transmission system, an enumeration-based searching approach is used to hunt for the optimal working points for both motors to maximize the overall efficiency. Like many energy management strategies, approaches that focus on reducing energy consumption can result in frequent gearshifts. To improve drivability and make a balance between energy consumption and gearshifts, a cost function is designed. To verify the effectiveness of the proposed method, a mathematical model is built, and the simulation results demonstrate the achieved improvements.


2021 ◽  
Vol 13 (2) ◽  
pp. 168781402199438
Author(s):  
Chaofeng Pan ◽  
Yuanxue Tao ◽  
Limei Wang ◽  
Huanhuan Li ◽  
Jufeng Yang

Energy management strategy is developed by considering the random and air conditioning load fluctuation, which greatly affected the torque control of the electric motor in electric vehicle. Firstly, the vehicle power consumption model is established, based on the influencing factors of electric vehicle energy consumption: random load and air conditioning load. Therefore, driving conditions with random characteristics representing the actual random load are constructed. According to the clustered characteristic parameters, the driving conditions were classified as different driving modes. Secondly, the mode of predicted condition was taken as a variable to evaluate the logic threshold strategy and fuzzy control strategy in which the influence of air conditioning was considered. Finally, under the condition of New European Driving Cycle (NEDC), the proposed management strategy was simulated in software environment, and the hardware in-loop (HIL) test was performed to verify the strategy. The simulation and HIL test results show that the proposed energy management strategy can increase the driving range by considering the load fluctuation of air conditioning. Furthermore, the strategy combining the driving mode prediction can alleviate the decline rate of SOC. And the fuzzy control strategy has better adaptability in complex conditions and lower battery energy consumption rate.


Energy ◽  
2013 ◽  
Vol 55 ◽  
pp. 58-67 ◽  
Author(s):  
Chrysovalantou Ziogou ◽  
Dimitris Ipsakis ◽  
Panos Seferlis ◽  
Stella Bezergianni ◽  
Simira Papadopoulou ◽  
...  

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