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.

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.

Receding Horizon Real-Time Energy Management Strategy for Hybrid Vehicles

2013 ◽  
Author(s):  
Bram de Jager ◽  
Thijs van Keulen
Keyword(s):  
Real Time ◽  
Energy Management ◽  
Management Strategy ◽  
Hybrid Vehicles ◽  
State Control ◽  
Energy Management Strategy ◽  
Receding Horizon ◽  
Fuel Use ◽  
Commodity Hardware ◽  
The Future

Indirect optimal control and dynamic programming are combined in a receding horizon controller to obtain an energy management strategy for hybrid vehicles. This combination permits the use of inaccurate predictions of the future, instead of requiring exact knowledge, and allows the use of mixed state-control constraints, like voltage constraints for batteries. The controller can run in real-time on commodity hardware and, using a prediction of the future based on geographic information only, obtains a fuel use within 0.2% of the optimal fuel use computed with the exact speed and power trajectory of the vehicle known in advance. All this for a planned distance of more than 500 [km].

scholarly journals Development of Global Optimization Algorithm for Series-Parallel PHEV Energy Management Strategy Based on Radau Pseudospectral Knotting Method

Energies ◽  
2019 ◽  
Vol 12 (17) ◽  
pp. 3268
Author(s):  
Kegang Zhao ◽  
Jinghao Bei ◽  
Yanwei Liu ◽  
Zhihao Liang
Keyword(s):  
Global Optimization ◽  
Energy Management ◽  
Computational Efficiency ◽  
Management Strategy ◽  
Hybrid Electric Vehicles ◽  
Minimum Principle ◽  
Management Strategies ◽  
Energy Management Strategy ◽  
Pontryagin Minimum Principle ◽  
Component Sizing

The powertrain model of the series-parallel plug-in hybrid electric vehicles (PHEVs) is more complicated, compared with series PHEVs and parallel PHEVs. Using the traditional dynamic programming (DP) algorithm or Pontryagin minimum principle (PMP) algorithm to solve the global-optimization-based energy management strategies of the series-parallel PHEVs is not ideal, as the solution time is too long or even impossible to solve. Chief engineers of hybrid system urgently require a handy tool to quickly solve global-optimization-based energy management strategies. Therefore, this paper proposed to use the Radau pseudospectral knotting method (RPKM) to solve the global-optimization-based energy management strategy of the series-parallel PHEVs to improve computational efficiency. Simulation results showed that compared with the DP algorithm, the global-optimization-based energy management strategy based on the RPKM improves the computational efficiency by 1806 times with a relative error of only 0.12%. On this basis, a bi-level nested component-sizing method combining the genetic algorithm and RPKM was developed. By applying the global-optimization-based energy management strategy based on RPKM to the actual development, the feasibility and superiority of RPKM applied to the global-optimization-based energy management strategy of the series-parallel PHEVs were further verified.

Investigation on the Energy Management Strategy for Hydraulic Hybrid Wheel Loaders

2013 ◽  
Author(s):  
Feng Wang ◽  
Mohd Azrin Mohd Zulkefli ◽  
Zongxuan Sun ◽  
Kim A. Stelson
Keyword(s):  
Energy Management ◽  
Hydraulic System ◽  
Management Strategy ◽  
Energy Management Strategy ◽  
Road Vehicles ◽  
Engine Operation ◽  
Wheel Loader ◽  
Hydraulic Hybrid ◽  
Power Split ◽  
Wheel Loaders

Energy management strategies for a hydraulic hybrid wheel loader are studied in this paper. The architecture of the hydraulic hybrid wheel loader is first presented and the differences of the powertrain and the energy management system between on-road vehicles and wheel loaders are identified. Unlike the on-road vehicles where the engine only powers the drivetrain, the engine in a wheel loader powers both the drivetrain and the working hydraulic system. In a non-hybrid wheel loader, the two sub-systems interfere with each other since they share the same engine shaft. By using a power split drivetrain, it not only allows for optimal engine operation and regenerative braking, but also eliminates interferences between driving and working functions, which improve the productivity, fuel efficiency and operability of the wheel loader. An energy management strategy (EMS) based on dynamic programming (DP) is designed to optimize the operation of both the power split drivetrain and the working hydraulic system. A short loading cycle is selected as the duty cycle. The EMS based on DP is compared with a rule-based strategy through simulation.

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