Optimization-Based Energy Management Strategy for a 48-V Mild Parallel Hybrid Electric Power System

2020 ◽  
Vol 142 (5) ◽  
Author(s):  
Ying Wang ◽  
Zhiyong Huang
Keyword(s):  
Global Optimization ◽  
Real Time ◽  
Energy Management ◽  
Management Strategy ◽  
Electric Power System ◽  
Energy Management Strategy ◽  
Powertrain System ◽  
Study Results ◽  
Hybrid Electric ◽  
Mild Hybrid

Abstract The application of a 48-V mild hybrid powertrain system is one of the eco-friendly technologies for global CO2 reduction in the present sector of hybrid electric vehicles (HEVs). It is well known that the energy management strategy is crucial for improving the fuel economy of the HEVs. Therefore, the strengths and the limitations of dynamic programming (DP) global optimization strategy and adaptive equivalent consumption minimization strategy (ECMS) for this kind of powertrain system under new European driving cycle (NEDC) and federal test procedure (FTP75) driving cycles are discussed in this paper. The results of the DP global optimization solution have also been adopted as a reference for evaluating the degree of optimality of real-time controllers. The reference start of charge (SOC) was found to be a very important parameter for the real-time ECMS approach. Thus, an adaptive ECMS approach using the SOC obtained from DP global optimization algorithm as a reference SOC in real-time ECMS control was studied. The study results in this paper may provide some theoretical support for future energy management optimization of a 48-V mild hybrid parallel powertrain system.

scholarly journals Real-time Energy Management Strategy for Oil-Electric-Liquid Hybrid System based on Lowest Instantaneous Energy Consumption Cost

Energies ◽  
2020 ◽  
Vol 13 (4) ◽  
pp. 784 ◽  
Author(s):  
Yang Yang ◽  
Zhen Zhong ◽  
Fei Wang ◽  
Chunyun Fu ◽  
Junzhang Liao
Keyword(s):  
Global Optimization ◽  
Real Time ◽  
Energy Management ◽  
Management Strategy ◽  
Threshold Energy ◽  
Energy Management Strategy ◽  
Hydraulic Hybrid ◽  
Consumption Cost ◽  
Saving Effect ◽  
Instantaneous Energy

For the oil–electric–hydraulic hybrid power system, a logic threshold energy management strategy based on the optimal working curve is proposed, and the optimal working curve in each mode is determined. A genetic algorithm is used to determine the optimal parameters. For driving conditions, a real-time energy management strategy based on the lowest instantaneous energy cost is proposed. For braking conditions and subject to the European Commission for Europe (ECE) regulations, a braking force distribution strategy based on hydraulic pumps/motors and supplemented by motors is proposed. A global optimization energy management strategy is used to evaluate the strategy. Simulation results show that the strategy can achieve the expected control target and save about 32.14% compared with the fuel consumption cost of the original model 100 km 8 L. Under the New European Driving Cycle (NEDC) working conditions, the energy-saving effect of this strategy is close to that of the global optimization energy management strategy and has obvious cost advantages. The system design and control strategy are validated.

scholarly journals An Application of the ECMS Strategy to a Wankel Hybrid Electric UAV

2019 ◽  
Vol 304 ◽  
pp. 03010
Author(s):  
Teresa Donateo ◽  
Claudia Lucia De Pascalis ◽  
Antonio Ficarella
Keyword(s):  
Electric Power ◽  
Energy Management ◽  
Lithium Batteries ◽  
Management Strategy ◽  
Electric Power System ◽  
Thermal Converter ◽  
Energy Management Strategy ◽  
Aerial Vehicle ◽  
Hybrid Electric ◽  
Wankel Engine

In a previous work, the authors optimized the hybrid electric power system for a tactical Unmanned Aerial Vehicle including a Wankel engine as thermal converter and a permanent magnet electric motor powered by lithium batteries. Startingfrom this optimal configuration, we address here the topic of a refined optimization of the energy management strategy, i.e. the contribution of the battery to the required power in each segment of the flight. The Equivalent Consumption Minimization Strategy (ECMS) was chosen with the goal of minimizing fuel consumption while fully depleting the energy stored in the battery from the beginning to the end of each mission.

scholarly journals A Real Time Energy Management Strategy for Plug-in Hybrid Electric Vehicles based on Optimal Control Theory

2014 ◽  
Vol 45 ◽  
pp. 949-958 ◽  
Author(s):  
Laura Tribioli ◽  
Michele Barbieri ◽  
Roberto Capata ◽  
Enrico Sciubba ◽  
Elio Jannelli ◽  
...  
Keyword(s):  
Optimal Control ◽  
Control Theory ◽  
Real Time ◽  
Energy Management ◽  
Electric Vehicles ◽  
Optimal Control Theory ◽  
Management Strategy ◽  
Hybrid Electric Vehicles ◽  
Energy Management Strategy ◽  
Hybrid Electric

scholarly journals Smart Energy Management for Series Hybrid Electric Vehicles Based on Driver Habits Recognition and Prediction

Energies ◽  
2020 ◽  
Vol 13 (11) ◽  
pp. 2954
Author(s):  
Loïc Joud ◽  
Rui Da Silva ◽  
Daniela Chrenko ◽  
Alan Kéromnès ◽  
Luis Le Moyne
Keyword(s):  
Experimental Study ◽  
Dynamic Programming ◽  
Real Time ◽  
Energy Management ◽  
Control Strategy ◽  
Management Strategy ◽  
Energetic Efficiency ◽  
Energy Management Strategy ◽  
Common Cycles ◽  
Hybrid Electric

The objective of this work is to develop an optimal management strategy to improve the energetic efficiency of a hybrid electric vehicle. The strategy is built based on an extensive experimental study of mobility in order to allow trips recognition and prediction. For this experimental study, a dedicated autonomous acquisition system was developed. On working days, most trips are constrained and can be predicted with a high level of confidence. The database was built to assess the energy and power needed based on a static model for three types of cars. It was found that most trips could be covered by a 10 kWh battery. Regarding the optimization strategy, a novel real time capable energy management approach based on dynamic vehicle model was created using Energetic Macroscopic Representation. This real time capable energy management strategy is done by a combination of cycle prediction based on results obtained during the experimental study. The optimal control strategy for common cycles based on dynamic programming is available in the database. When a common cycle is detected, the pre-determined optimum strategy is applied to the similar upcoming cycle. If the real cycle differs from the reference cycle, the control strategy is adapted using quadratic programming. To assess the performance of the strategy, its resulting fuel consumption is compared to the global optimum calculated using dynamic programming and used as a reference; its optimality factor is above 98%.

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