Comparisons of Energy Management Methods for a Parallel Plug-In Hybrid Electric Vehicle between the Convex Optimization and Dynamic Programming

Xiao, Renxin; Liu, Baoshuai; Shen, Jiangwei; Guo, Ningyuan; Yan, Wensheng; Chen, Zheng

doi:10.3390/app8020218

Cited by 33 publications

(27 citation statements)

References 39 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The proposed algorithm was 17 times faster than conventional methods. A comparative analysis of Convex optimization and Dynamic-programming method for energy management system was done in [32]. Non-linear relation of ICE fuel rate and battery charging power for various speed level was designed by using convex optimization.…”

Section: Modeling Of Hybrid Vehiclementioning

confidence: 99%

Fuel efficiency optimization Techniques in Hybrid Vehicle

Srivastava*¹,

Maurya²

2019

IJRTE

View full text Add to dashboard Cite

The hybrid electric vehicle (HEV) has the potential of sufficing drive needs with better fuel efficiency. The complex nature of hybrid vehicle provides multiple opportunities for obtaining better fuel efficiency. The mathematical modeling is a necessity for understanding the behavior of HEV. The fuel efficiency is obtained through various means including the design of energy management system, component sizing, emission control, and other methods. In the present paper, a mathematical model of HEV is presented for a parallel HEV with a review of various methods used for fuel efficiency optimization.

show abstract

Section: Modeling Of Hybrid Vehiclementioning

confidence: 99%

Fuel efficiency optimization Techniques in Hybrid Vehicle

Srivastava*¹,

Maurya²

2019

IJRTE

View full text Add to dashboard Cite

show abstract

“…Hybrid electric vehicles (HEV) have been widely adopted by the automotive industry as a practical solution to increasing fuel efficiency and extending driving range [1][2][3][4][5][6][7][8]. However, because the configuration is more complicated, if the design is not properly executed torsional vibration problems are more likely to occur, such as torsional damper damage and broken shafts, but it also provides a new means for torsional vibration control [9][10][11].…”

Section: Motivations and Technical Challengesmentioning

confidence: 99%

Simulation Model and Method for Active Torsional Vibration Control of an HEV

2018

View full text Add to dashboard Cite

Hybrid electric vehicles (HEV) might cause new noise vibration and harshness (NVH) problems, due to their complex powertrain systems. Therefore, in this paper, a new longitudinal dynamic simulation model of a series-parallel hybrid electric bus with an active torsional vibration control module is proposed. First, the schematic diagrams of the simulation model architecture and the active control strategy are given, and the dynamic models of the main components are introduced. Second, taking advantage of the characteristics of hybrid systems, a method of determining the key dynamic parameters by a bench test is proposed. Finally, in a typical bus-driving cycle for Chinese urban conditions, time domain and frequency domain processing methods are used to analyze vehicle body jerk, fluctuation of rotational speed, and torsional angle of the key components. The results show that the active control method can greatly improve the system’s torsional vibration performance when switching modes and at resonance.

show abstract

“…Other researchers extended their optimizations beyond the EMS by finding the best power sources combination for optimal energy saving, using rule based methods, fuzzy logic control, genetic algorithm, particle swarm algorithms, and two‐dimensional pontryagin's minimum principle . Others used different versions of dynamic programming to achieve the optimal sizes while reducing operational costs . Fares et al developed an efficient EMS using a DP technique.…”

Section: Introductionmentioning

confidence: 99%

Power sources sizing for a fuel cell hybrid vehicle

2020

View full text Add to dashboard Cite

Fuel cell hybrid vehicles (FCHV) are attractive alternatives to fossil fuel based ones in terms of lowering levels of polluting emissions. This paper presents a methodology for modeling, sizing, and power management of FCHV. The aim of the study is to achieve the lowest cost of driving over different driving cycles taking into consideration the vehicle specifications and minimum drivability constraints. The tunnel dynamic programming (TDP) is used to find the optimal power split between the battery and the fuel cell to meet the power demand for driving. On the other hand, since cost is a major barrier hindering the commercialization of FCHV, Pareto front is used to determine the best combination of sizes to achieve the lowest operational cost. The analysis covers different driving cycles including a combination of the highway and urban driving cycles mimicking a realistic one. The focus on lithium titanate battery and the combination of TDP‐Pareto front are the significant contributions of this paper. Comparative results against a commercial hybrid vehicle showed that the proposed model found a more efficient design in terms of hydrogen consumption and more capable in meeting aggressive drivability constraints as the electric motor size selected is greater.

show abstract

Comparisons of Energy Management Methods for a Parallel Plug-In Hybrid Electric Vehicle between the Convex Optimization and Dynamic Programming

Cited by 33 publications

References 39 publications

Fuel efficiency optimization Techniques in Hybrid Vehicle

Fuel efficiency optimization Techniques in Hybrid Vehicle

Simulation Model and Method for Active Torsional Vibration Control of an HEV

Power sources sizing for a fuel cell hybrid vehicle

Contact Info

Product

Resources

About