Improved Energy Management Strategy of Hybrid Electric Vehicles with Varying Terrain

Biswas, Dhrupad; Sengupta, Somnath; Mitra, Desham; Mukhopadhyay, Siddhartha

doi:10.1016/j.ifacol.2018.10.147

Cited by 5 publications

(4 citation statements)

References 10 publications

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“…The required ICE speed is determined by matching the signal generated in the drive cycle to the ICE speed using the 1-D lookup table block in MATLAB/Simulink, and also the PI-controller of the motor is handling the difference between the required motor speed and the actual motor speed. The required motor speed is determined by using (7), where V in this equation is the required speed in the drive cycle. While the function of checking operating conditions in Motor_mode is to compare the power required by the vehicle at the speed under 45 km/h with  ISSN: 2088-8708 Int J Elec & Comp Eng, Vol.…”

Section: Simulation Resultsmentioning

confidence: 99%

“…The ICE is connected to the carrier gear of the planetary gear set. Because of this connection, the ICE's power is used to propel the vehicle and to charge the batteries [7]. In addition, the speed of ICE affects the selection of generator specifications, because they are connected by the planetary gear set, and this may lead to the generator being operated at higher speeds than the designed speed when the appropriate speed specifications are not chosen for the generator.…”

Section: Powertrain Of the Series-parallel Hev 221 Internal Combustio...mentioning

confidence: 99%

“…These rules are set by heuristics or mathematical models. This is an easy-to-implement and computationally fast strategy because it is implemented by lookup tables [6], [7]. The supervisory level contains entries that are processed by the rules in the rule-based strategy to obtain logical outputs to control the on or off of each of the ICE, motor, and generator.…”

Section: Rule-based Control Strategymentioning

confidence: 99%

“…This strategy is based on the idea of energy flow according to the operating mode and SOC, where the energy required for the vehicle is calculated and how it is provided from the energy sources in the vehicle according to this strategy. In addition, in study [7] rule-based strategy is used to drive a model of a series-parallel HEV, where this strategy works to provide the torque required by the vehicle through a distribution between the ICE and motor or by the motor only, depending on the load conditions and SOC. Similarly, the study [8] also explains how to build a control unit to drive a series-parallel HEV using a rule-based strategy whereby this unit decides the vehicle's propulsion mechanism either using the electric motor only or by the ICE and the motor together, these decisions are made depending on the inputs of this unit where the torque required by the vehicle and SOC are considered as inputs to this unit.…”

Section: Introductionmentioning

confidence: 99%

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Energy management for hybrid electric vehicles using rule based strategy and PI control tuned by particle swarming optimization algorithm

Al-Flehawee

Al-Mayyahi

2022

IJECE

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<span lang="EN-US">Recently, hybrid electric vehicles are increasingly being used to replace conventional vehicles. In this paper, a control methodology is designed that can reduce fuel consumption and improve the vehicle’s dynamic response. As the control unit based on this methodology consists of two levels, the first depends on the application of a rule-based strategy for energy management between the main components of the vehicle, and this strategy is based on a set of rules that are activated according to parameters such as vehicle speed and the battery <a name="_Hlk108852620"></a>state of charge (SOC) that control the activation/deactivation of the internal combustion engine (ICE), motor, and generator. This level also makes ICE operate at operation points with high efficiency, which is represented by the optimal operating line (OOL). The second level is called the low control level, and it consists of two proportional-integral (PI) controllers used to control the speed of each ICE and the motor to obtain the appropriate torque for both of them to drive the vehicle properly. The particle swarming optimization (PSO) algorithm is utilized to tune the parameters of the PI controllers. The obtained results have effectively minimized fuel consumption and improved the performance of the vehicle.</span>

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Section: Simulation Resultsmentioning

confidence: 99%

Section: Powertrain Of the Series-parallel Hev 221 Internal Combustio...mentioning

confidence: 99%