Battery Management System for Future Electric Vehicles, Volume II
A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Energy Science and Technology".
Deadline for manuscript submissions: closed (30 April 2021) | Viewed by 4862
Special Issue Editors
Interests: control of energy flows—hybrid powertrains and wind turbine control; diagnostics and prognostics of technical systems; modeling, diagnosis, and control of elastic mechanical structures; control theory: robust observers and nonlinear control; cognitive technical systems: automata and assistance
Special Issues, Collections and Topics in MDPI journals
Interests: power management, control, and optimization of electric and hybrid vehicles; battery management; advanced driver assistance systems
Special Issue Information
Dear Colleagues,
Considering the threat of polluting emissions and energy dependence, the electrification of road transport has become a global focus. The main performance parameters of electric vehicles (EVs) include size, cost, charging time, energy consumption, and efficiency. With batteries being a crucial component in EVs, evaluating the influence of the charging–discharging pattern on battery usage, performance, safety, and life is vital. The primary tasks of battery management systems (BMS) include ensuring safety and reliability by accurate state estimation and monitoring; extending end of life (EoL) by minimizing aging, fault detection and alarm; thermal management; information storage; and networking between the modules.
For future EV generations, additional control features are required to optimize charging–discharging patterns to extend battery life and decrease battery cost, while also providing maximum usability. It can be assumed that detailed real and virtual cell-level monitoring and control will be relevant.
Current BMS are based on standard cycle tests. From the results it is difficult to predict the remaining useful life when subjected to unknown drive patterns and cycles; thermal management is another issue particularly during fast charging.
This Special Issue aims to address the recent developments in battery modeling; parameter estimation; prediction of remaining useful life; and related control algorithms for power, lifetime, and thermal management. Contributions related to charging approaches and their effects on battery performance are also welcome. Innovative hybridization concepts to assist, protect, and/or extend battery life and/or performance will also be encouraged.
To perfect the Special Issue “Battery Management System for Future Electric Vehicles”, contributions should be clearly focused on the addressed research areas. Contributions should not be focused on technological state-of-the-art systems, pure numerical simulations studies using know formulas, application reports, or known battery charging/discharging strategies, and should not only repeat known results (from previous works or the work of others). Prospective authors should provide original work with significant and novel contributions, providing new facts, ideas, insights, and results.
Prof. Dr. Dirk Söffker
Dr. Bedatri Moulik
Guest Editors
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Keywords
- Battery management
- Battery modeling
- Battery state estimation
- Battery monitoring
- Thermal management
- Hybrid electric vehicles, hybrid electric powertrains
- Complete battery system modeling
- Generic battery models
- Cycle and calendar life, modeling, and control
- Lifetime modeling, remaining useful lifetime models and evaluations
- Charging approaches: models, experiments
- Filters-based prognosis of battery health
- Observer-based state estimation for complex nonlinear battery models
- Optimal charging-discharging cycles related to battery type
- Optimal component sizing for battery management
- Optimal hybridization schemes (in light of increasing capacities of SuperCaps and FCs) for better battery management
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