Sensitivity Analysis of Energy Management Strategies for Hydraulic Hybrid Vehicles

2012 ◽  
Author(s):  
Timothy O. Deppen ◽  
Andrew G. Alleyne ◽  
Kim A. Stelson ◽  
Jonathan J. Meyer
Keyword(s):  
Sensitivity Analysis ◽  
Energy Management ◽  
Management Strategies ◽  
Hybrid Vehicles ◽  
Hydraulic Hybrid

Rule-based energy management strategies for hybrid vehicles

2007 ◽  
Vol 1 (1) ◽  
pp. 71 ◽  
Author(s):  
Theo Hofman ◽  
Maarten Steinbuch ◽  
Roell Van Druten ◽  
Alex Serrarens
Keyword(s):  
Energy Management ◽  
Management Strategies ◽  
Hybrid Vehicles ◽  
Rule Based

scholarly journals A 3D Printed Power-Split Device for Testing Energy Management Strategies Applied to Hybrid Vehicles

2015 ◽  
Vol 48 (29) ◽  
pp. 164-169
Author(s):  
Jose L. Torres ◽  
Francisco M. Arrabal ◽  
Jose L. Blanco ◽  
Antonio Gimenez
Keyword(s):  
Energy Management ◽  
Management Strategies ◽  
Hybrid Vehicles ◽  
Power Split ◽  
3D Printed

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.

Energy Management Strategies for Parallel Hybrid Vehicles Using Fuzzy Logic

2000 ◽  
Vol 33 (26) ◽  
pp. 83-88
Author(s):  
Niels J. Schouten ◽  
Mutasim A. Salman ◽  
Naim A. Kheir
Keyword(s):  
Fuzzy Logic ◽  
Energy Management ◽  
Management Strategies ◽  
Hybrid Vehicles ◽  
Parallel Hybrid

Comparative Study of Energy Management Strategies for Hydraulic Hybrids

2014 ◽  
Vol 137 (4) ◽  
Author(s):  
Timothy O. Deppen ◽  
Andrew G. Alleyne ◽  
Jonathan J. Meyer ◽  
Kim A. Stelson
Keyword(s):  
Energy Management ◽  
Design Method ◽  
Tracking Error ◽  
Management Strategies ◽  
Stochastic Dynamic ◽  
Drive Cycle ◽  
Hybrid Powertrain ◽  
Hydraulic Hybrid ◽  
System A ◽  
Factorial Design Of Experiments

The sensitivity of energy management strategies (EMS) with respect to variations in drive cycle and system parameters is considered. The design of three strategies is presented: rule-based, stochastic dynamic programming (SDP), and model predictive control (MPC). Each strategy is applied to a series hydraulic hybrid powertrain and validated experimentally using a hardware-in-the-loop system. A full factorial design of experiments (DOE) is conducted to evaluate the performance of these controllers under different urban and highway drive cycles as well as with enforced modeling errors. Through this study, it is observed that each EMS design method represents a different level of tradeoff between optimality and robustness based on how much knowledge of the system is assumed. This tradeoff is quantified by analyzing the standard deviation of system specific fuel consumption (SSFC) and root mean square (RMS) tracking error over the different simulation cases. This insight can then be used to motivate the choice of which control strategy to use based on the application. For example, a city bus travels a repeated route and that knowledge can be leveraged in the EMS design to improve performance. Through this study, it is demonstrated that there is not one EMS design method which is best suited for all applications but rather the underlying assumptions of the system and drive cycle must be carefully considered so that the most appropriate design method is chosen.

scholarly journals A Review of Optimal Energy Management Strategies for Hybrid Electric Vehicle

2014 ◽  
Vol 2014 ◽  
pp. 1-19 ◽  
Author(s):  
Aishwarya Panday ◽  
Hari Om Bansal
Keyword(s):  
Energy Management ◽  
Electric Vehicles ◽  
Fuel Economy ◽  
Hybrid Electric Vehicles ◽  
Control Strategies ◽  
Management Strategies ◽  
Energy Optimization ◽  
Hybrid Vehicles ◽  
Power Split ◽  
Hybrid Electric

Presence of an alternative energy source along with the Internal Combustion Engine (ICE) in Hybrid Electric Vehicles (HEVs) appeals for optimal power split between them for minimum fuel consumption and maximum power utilization. Hence HEVs provide better fuel economy compared to ICE based vehicles/conventional vehicle. Energy management strategies are the algorithms that decide the power split between engine and motor in order to improve the fuel economy and optimize the performance of HEVs. This paper describes various energy management strategies available in the literature. A lot of research work has been conducted for energy optimization and the same is extended for Plug-in Hybrid Electric Vehicles (PHEVs). This paper concentrates on the battery powered hybrid vehicles. Numerous methods are introduced in the literature and based on these, several control strategies are proposed. These control strategies are summarized here in a coherent framework. This paper will serve as a ready reference for the researchers working in the area of energy optimization of hybrid vehicles.

Sign in / Sign up

Export Citation Format

Share Document