Energy Management Strategy of Hydraulic Hybrid Vehicles Based on Instantaneous Equivalent Fuel Consumption Minimization

2013 ◽  
Vol 7 (3) ◽  
pp. 99-104
Author(s):  
Xiang-sheng Li ◽  
Dou Chen ◽  
Yong-jun Zhou
Keyword(s):  
Fuel Consumption ◽  
Energy Management ◽  
Management Strategy ◽  
Hybrid Vehicles ◽  
Energy Management Strategy ◽  
Hydraulic Hybrid ◽  
Equivalent Fuel ◽  
Equivalent Fuel Consumption

scholarly journals A Rule-Based Energy Management Strategy Based on Dynamic Programming for Hydraulic Hybrid Vehicles

2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
Haicheng Zhou ◽  
Zhaoping Xu ◽  
Liang Liu ◽  
Dong Liu ◽  
Lingling Zhang
Keyword(s):  
Dynamic Programming ◽  
Energy Management ◽  
Management Strategy ◽  
Optimal Solution ◽  
Hybrid Vehicles ◽  
Engine Control ◽  
Energy Management Strategy ◽  
Rule Based ◽  
Hydraulic Hybrid ◽  
Global Optimal

Energy management strategy is very important for hydraulic hybrid vehicles to improve fuel economy. The rule-based energy management strategies are widely used in engineering practice due to their simplicity and practicality. However, their performances differ a lot from different parameters and control actions. A rule-based energy management strategy is designed in this paper to realize real-time control of a novel hydraulic hybrid vehicle, and a control parameter selection method based on dynamic programming is proposed to optimize its performance. Firstly, the simulation model of the hydraulic hybrid vehicle is built and validated by the data tested from prototype experimental platform. Based on the simulation model, the optimization method of dynamic programming is used to find the global optimal solution of the engine control for the UDDS drive cycle. Then, the engine control parameters of the rule-based energy management strategy are selected according to the engine control trajectory of the global optimal solution. The simulation results show that the 100 km fuel consumption of the proposed rule-based energy management strategy is 12.7L, which is very close to the global optimal value of 12.4L and is suboptimal.

scholarly journals Evaluation of a Modified Equivalent Fuel-Consumption Minimization Strategy Considering Engine Start Frequency and Battery Parameters for a Plugin Hybrid Two-Wheeler

Energies ◽  
2020 ◽  
Vol 13 (12) ◽  
pp. 3122
Author(s):  
Naga Kavitha Kommuri ◽  
Andrew McGordon ◽  
Antony Allen ◽  
Dinh Quang Truong
Keyword(s):  
Fuel Consumption ◽  
Energy Management ◽  
Fuel Economy ◽  
Management Strategies ◽  
Optimum Operating ◽  
Energy Management Strategy ◽  
Rule Based ◽  
Equivalent Fuel ◽  
Equivalent Fuel Consumption ◽  
Two Wheeler

An appropriate energy management strategy is essential to enhance the performance of hybrid electric vehicles. A novel modified equivalent fuel-consumption minimization strategy (ECMS) is developed considering the engine operating point deviation from the optimum operating line. This paper focuses on an all-inclusive evaluation of this modified ECMS with other state-of-art energy management strategies concerning battery ageing, engine switching along with fuel economy and charge sustenance. The simulation-based results of a hybrid two-wheeler concept are analysed, which shows that the modified ECMS offers the highest benefit compared to rule-based controllers concerning fuel economy and reduction in engine switching events. However, the improvement in fuel economy using modified ECMS has significant negative potential effects on critical battery parameters influencing battery ageing. The results are analysed and found consistent for two different drive cycles and three different powertrain component configurations. The results show a significant reduction in fuel consumption of up to 21.18% and a reduction in engine switching events of up to 55% with modified ECMS when compared with rule-based strategies. However, there is a significant increase in battery temperature by 31% and battery throughput by 378%, which plays a major role in accelerating battery ageing. This paper emphasizes the need to consider battery-ageing parameters along with other control objectives for a robust assessment of energy management strategies. This study helps in laying down a foundation for future improvements in energy management development and it also aids in establishing a basis for comparing energy management controllers.

scholarly journals Power-Following Control Strategy of a Wheel-Drive Hydraulic Hybrid Vehicle

2020 ◽  
Vol 66 (3) ◽  
pp. 193-202
Author(s):  
Tao Zhang ◽  
Qiang Wang ◽  
Xiao-Hui He ◽  
Si-Sheng Li ◽  
Xin-Min Shen
Keyword(s):  
Fuel Consumption ◽  
Energy Management ◽  
Fuel Economy ◽  
Control Strategy ◽  
Management Strategy ◽  
Dynamic Performance ◽  
Energy Management Strategy ◽  
Hydraulic Hybrid ◽  
Wheel Drive ◽  
Critical Technology

Energy management strategy is a critical technology for improving the fuel economy of wheel-drive hydraulic hybrid vehicles. For driving, a power-following control strategy is proposed in this study by adding several working points of the engine in the optimal fuel economy power curve. For braking, the “I” curve distribution strategy based on critical braking strength zmin was adopted. A test bench was constructed according to the quarter of the prototype vehicle. Taking the typical working conditions of Federal Urban Driving Schedule (FUDS) and the selfset extra-urban driving schedule (EUDC-1) cycle condition into consideration, the energy management strategy was studied. The torque and speed of the simulated engine and pressure of the accumulator were obtained. The test fuel consumption in this research was compared with the original fuel consumption of the prototype vehicle. It was found that the proposed energy management strategy could effectively improve the fuel economy by more than 24 % under the requirement of satisfying the dynamic performance of the whole vehicle.

scholarly journals An Effective Energy Management Strategy Based on Mine-Blast Optimization Technique Applied to Hybrid PEMFC/Supercapacitor/Batteries System

Energies ◽  
2019 ◽  
Vol 12 (19) ◽  
pp. 3796 ◽  
Author(s):  
Ahmed M. Nassef ◽  
Ahmed Fathy ◽  
Hegazy Rezk
Keyword(s):  
Energy Management ◽  
Fuel Economy ◽  
Management Strategy ◽  
Optimization Technique ◽  
Effective Energy ◽  
Hydrogen Fuel ◽  
Energy Management Strategy ◽  
Equivalent Fuel ◽  
Overall Efficiency ◽  
Equivalent Fuel Consumption

An effective energy management strategy based on the mine-blast optimization (MBA) technique was proposed in this paper to optimally manage the energy in a hybrid power system. The hybrid system was composed of fuel cells, batteries, and supercapacitors. Such system was employed to supply highly fluctuated load. The results of the proposed strategy were compared with previously employed strategies such as fuzzy logic control (FLC), state machine control strategy (SMCS), and equivalent fuel consumption minimization strategy (ECMS). The comparison was carried out in terms of the hydrogen fuel economy and the overall efficiency as the key factors. The resulting responses of the proposed MBA-based management strategy indicate that its performance is the best among the other strategies of SMCS, FLC, and ECMS in both the hydrogen fuel economy and overall efficiency.

Collaborative optimization and energy management of hydraulic hybrid mining trucks

2021 ◽  
pp. 095440702110585
Author(s):  
Hongliang Li ◽  
Denglin Zhu ◽  
Lihua Shang ◽  
Ping Fan
Keyword(s):  
Fuel Consumption ◽  
Energy Management ◽  
Extraction Method ◽  
Management Strategy ◽  
Transmission System ◽  
Collaborative Optimization ◽  
Energy Management Strategy ◽  
System Parameters ◽  
Hydraulic Hybrid ◽  
Driving Conditions

This article discusses the fuel economy optimization of a parallel hydraulic hybrid mining truck (HHMT). Considering the influences of various coupled factors, such as the transmission system, energy management strategy, and driving conditions, on the optimization goal, this article proposes the use of a double-layer optimization strategy with a collaborative optimization algorithm that combines particle swarm optimization (PSO) and a dynamic programming algorithm (DP) to eliminate the mutual effects of these coupled factors. A two-layer optimization model is developed, with powertrain parameters and energy management parameters as the optimization variables and the average fuel consumption under various driving conditions as the target. This model combines a variety of driving conditions to perform global optimization of the transmission system parameters while calculating the optimal energy distribution and analyzing the influences of various factors on the optimization goal. To achieve real-time and reliable control of energy management, the optimal energy management strategy rules obtained under various driving conditions are integrated and extracted, and an improved extraction method compared with the traditional extraction method is proposed. Finally, a rule-based energy management strategy is established. The strategy and optimized transmission system parameters are simulated and verified using a MATLAB and AMESIM joint simulation platform, and the effect of the rule strategy is evaluated. The obtained fuel consumption results are close to the results obtained by PSO-DP optimization, and the strategy is robust. The experiment verifies the effectiveness, feasibility and reliability of the optimization scheme, and extraction rule control strategy.

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].

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