Optimal energy management for a flywheel-assisted battery electric vehicle

Abstract

This is the accepted version of the paper.This version of the publication may differ from the final published version. Permanent AbstractBattery electric vehicles (BEV) are crucial to the reduction of dependence on fossil fuels and for moving towards a zero emission transport system. Though BEV technology has been rapidly improving, the limited driving range and high cost are significant impediments to the popularity of electric vehicles. The battery is the main element which affects the range and cost of the vehicle. The batteries can provide either high power or high energy but not both. Hybridization of the energy source is one of the methods to improve the energy efficiency of the vehicle, which would involve combining a high energy battery with a high power source. High speed flywheels (FW) have attractive properties and low cost potential which makes them excellent secondary energy storage devices to be used in hybrid and electric vehicles. They are utilized to load level the battery so as to protect it from peak loads and enhance its capacity and life. The flywheel is coupled to the drive line with a continuous variable transmission (CVT). This paper presents the optimal energy management strategy (EMS) for a mechanically connected flywheel assisted BEV (FWBEV) powertrain. The optimization problem is complex due to factors such as the small storage capacity of flywheel, kinematic constraints and slipping of clutches. Dynamic programming is used to calculate the optimal control strategy for torque distribution during operation in real world driving cycles. The results show significant potential for reduction of energy consumption in extra-urban and highway cycles, while reducing battery peak loads during all cycles. The results give a benchmark of the energy saving potential for such a powertrain and insights into how a real sub-optimal controller can be designed.

Prolongation of Battery Lifetime for Electric Buses through Flywheel Integration

“…Besides stationary applications, the integration of FESS within the transport sector was examined as well. Dhand et al [18] integrated a flywheel into a BEV by a mechanical continuously variable transmission system. The dynamic programming control strategy reduced battery peak loads during all cycles, leading to potentially reducing the energy consumption in extra-urban and highway cycles.…”

Modelling and optimal energy-saving control of automotive air-conditioning and refrigeration systems

“…Furthermore, this fast and robust model predictive controller can always guarantee the minimum power consumption for A/C-R systems under any working conditions. Because of the relatively slow dynamics of the working conditions of A/C-R systems, this slowly changing power consumption information can be integrated into a power management strategy as the auxiliary power taken out of the energy storage system 24 for prediction of the state of charge to enhance the overall efficiency of the HEVs and EVs.…”

State of charge estimation of ultracapacitor based on forgetting factor recursive least square and extended Kalman filter algorithm at full temperature range

“…Hybrid storage systems have attracted researchers' attention because they can compensate for limitations of a single-energy storage component and develop advantages of components of multiple-energy storage system. Hybrid storage systems include many types, such as fuel cell combined with battery [4] , ultracapacitor combined with superconducting magnetic energy storage [5] , battery combined with ultracapacitor [6] , ultracapacitor combined with fuel cell [7] , flywheel combined with battery [8] , compressed air energy storage combined with battery [9] , ultracapacitor combined with flywheel and battery [10] , and battery combined with fuel cell and ultracapacitor [11] . Among them, ultracapacitor presents advantages of high power density and fast response speed, while battery shows high energy density but need a long time to response.…”