Developing a Health-Conscious Energy Management Strategy Based on Prognostics for a Battery/Fuel Cell Hybrid Electric Vehicle

Yue, Meiling; Jemeï, Samir; Gouriveau, Rafael; Zerhouni, Noureddine

doi:10.1109/vppc.2018.8604987

Cited by 10 publications

(4 citation statements)

References 20 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Several machine learning algorithms can be found in the literature to perform the battery SOH prognostics [32,[59][60][61][62][63]. In [64], the author uses Support Vector Regression (SVR) to estimate the battery Remaining Useful Life (RUL) and takes it into consideration in the energy management strategy of a Fuel cell Hybrid Electric Vehicle (FC-HEV). This prognostic is carried out on-board the vehicle using example data measured in the laboratory but also real time measurements.…”

Section: Review Of Machine Learning Methods: a Combination Of Models And Experimental Datamentioning

confidence: 99%

A Review of Battery State of Health Estimation Methods: Hybrid Electric Vehicle Challenges

Noura

Boulon

Jemeï

2020

WEVJ

146

View full text Add to dashboard Cite

To cope with the new transportation challenges and to ensure the safety and durability of electric vehicles and hybrid electric vehicles, high performance and reliable battery health management systems are required. The Battery State of Health (SOH) provides critical information about its performances, its lifetime and allows a better energy management in hybrid systems. Several research studies have provided different methods that estimate the battery SOH. Yet, not all these methods meet the requirement of automotive real-time applications. The real time estimation of battery SOH is important regarding battery fault diagnosis. Moreover, being able to estimate the SOH in real time ensure an accurate State of Charge and State of Power estimation for the battery, which are critical states in hybrid applications. This study provides a review of the main battery SOH estimation methods, enlightening their main advantages and pointing out their limitations in terms of real time automotive compatibility and especially hybrid electric applications. Experimental validation of an online and on-board suited SOH estimation method using model-based adaptive filtering is conducted to demonstrate its real-time feasibility and accuracy.

show abstract

Section: Review Of Machine Learning Methods: a Combination Of Models And Experimental Datamentioning

confidence: 99%

A Review of Battery State of Health Estimation Methods: Hybrid Electric Vehicle Challenges

Noura

Boulon

Jemeï

2020

WEVJ

146

View full text Add to dashboard Cite

show abstract

“…Other rule‐based strategies for FC vehicles include a research study by Yue et al [28] who developed an EMS that controls the FC output and reduces the degradation of the battery. They employ an FLC that uses 36 rules to set the FC current to one of nine possible levels.…”

Section: Ems and Power Source Degradationmentioning

confidence: 99%

Fuel cell vehicle energy management strategy based on the cost of ownership

Davis

Hayes

2019

IET Electrical Systems in Transportation

View full text Add to dashboard Cite

This study presents a novel energy management strategy (EMS) which outperforms the published strategies developed for an international technology challenge, IEEE Vehicular Technology Society (VTS) Motor Vehicles Challenge 2017. The objective of the strategy is to minimise the cost of ownership of a low-power (15 kW) fuel cell (FC)-battery electric vehicle. Both the fuel consumption cost and power sources degradation costs are combined to represent the total cost of ownership. The simple adaptive rule-based strategy optimises the FC operation during low-traction power operation and switches to battery charge-sustaining operation for high traction power operation. This minimises fuel consumption and increases the lifetimes of the FC and of the battery. The strategy is then compared with the EMS of the 2015 Toyota Mirai, and the challenge vehicle model is modified to capture the learnings from the Mirai. Finally, a cost-benefit analysis for a plug-in FC vehicle is considered in order to improve FC lifetimes and to reduce costs for short drive cycles.

show abstract

“…The intended benefits lie in recovering of valuable catalysts (platinium and ruthenium) while allowing the additional recovery of other relevant materials such as the membrane or the carbon support [11]. Some others technological locks persist, such as their degradations and failure modes [12,13], prognosis and lifespan [14], corrosion protection [15] and many others. To improved the system reliability one main solution lay in the fault-tolerance control, in order to bring correction to performance degradation and prevent the system to fail [16].…”

Section: Introductionmentioning

confidence: 99%

A review of adaptive neural control applied to proton exchange membrane fuel cell systems

Lin-Kwong-Chon

Grondin-Pérez

Kadjo

et al. 2019

Annual Reviews in Control

View full text Add to dashboard Cite

Developing a Health-Conscious Energy Management Strategy Based on Prognostics for a Battery/Fuel Cell Hybrid Electric Vehicle

Cited by 10 publications

References 20 publications

A Review of Battery State of Health Estimation Methods: Hybrid Electric Vehicle Challenges

A Review of Battery State of Health Estimation Methods: Hybrid Electric Vehicle Challenges

Fuel cell vehicle energy management strategy based on the cost of ownership

A review of adaptive neural control applied to proton exchange membrane fuel cell systems

Contact Info

Product

Resources

About