Transportation research. part c, emerging technologies

Plug-in hybrid electric vehicles (PHEVs) offer an immediate solution for emissions reduction and fuel displacement within the current infrastructure. Targeting PHEV powertrain optimization, a plethora of energy management strategies (EMSs) have been proposed. Although these algorithms present various levels of complexity and accuracy, they find a limitation in terms of availability of future trip information, which generally prevents exploitation of the full PHEV potential in real-life cycles. This paper presents a comprehensive analysis of EMS evolution toward blended mode (BM) and optimal control, providing a thorough survey of the latest progress in optimization-based algorithms. This is performed in the context of connected vehicles and highlights certain contributions that intelligent transportation systems (ITSs), traffic information, and cloud computing can provide to enhance PHEV energy management. The study is culminated with an analysis of future trends in terms of optimization algorithm development, optimization criteria, PHEV integration in the smart grid, and vehicles as part of the fleet.

Energy Management in Plug-in Hybrid Electric Vehicles: Recent Progress and a Connected Vehicles Perspective

A lumped-parameter electro-thermal model for cylindrical batteries

http://www-personal.umich.edu/%7Ehpeng/On-board%20state%20of%20health%20monitoring%20of%20lithium-ion%20batteries.pdf

On-board state of health monitoring of lithium-ion batteries using incremental capacity analysis with support vector regression

Energy management strategies of connected HEVs and PHEVs: Recent progress and outlook

Robust Takagi–Sugeno fuzzy control of a spark ignition engine

https://hal.archives-ouvertes.fr/hal-00905860/document

Optimal Energy Management Strategy including Battery Health through Thermal Management for Hybrid Vehicles

This paper proposes a supervisory control for hybrid electrical vehicle (HEV). It is based on Equivalent Consumption Minimization Strategy (ECMS) extended with a new state reflecting the thermal state of the engine. A new consumption law taking into account the losses due to low engine temperature is therefore included in the optimal control problem. The strategy is tested offline on a regulatory driving cycle, the results show an improvement on the consumption which confirm the relevance of the approach.

On the integration of optimal energy management and thermal management of hybrid electric vehicles

https://hal.archives-ouvertes.fr/hal-00286610/document

Support vector regression from simulation data and few experimental samples

Although internal combustion engines display high overall maximum global efficiencies, this potential cannot be fully exploited in automotive applications: in real conditions, the average engine load (and thus efficiency) is quite low and the kinetic energy during a braking phase is lost. This work presents a new hybrid pneumatic-combustion engine and the associated thermodynamic cycles, which is able to store energy in the form of compressed air. This energy can be issued from a braking phase or from a combustion phase at low power. The potential energy from the air tank can then be restored to start the engine, or charge the engine at full load. The regenerative breaking and the suppression of the idling phases could provide an improvement in terms of fuel economy as high as 15% or more if combined with engine downsizing.

/pdf/thermodynamic-simulation-of-a-hybrid-pneumatic-combustion-tjov7p0se4.pdf

Yann Chamaillard

Papers

Robust Takagi–Sugeno fuzzy control of a spark ignition engine

Optimal Energy Management Strategy including Battery Health through Thermal Management for Hybrid Vehicles

On the integration of optimal energy management and thermal management of hybrid electric vehicles

Support vector regression from simulation data and few experimental samples

Thermodynamic Simulation of a Hybrid Pneumatic-Combustion Engine Concept