Energy Management of a Parallel Hybrid Electric Vehicle using Model Predictive Static Programming

Biswas, Dhrupad; Ghosh, Susenjit; Sengupta, Somnath; Mukhopadhyay, Siddhartha

doi:10.1016/j.energy.2022.123505

Cited by 15 publications

(2 citation statements)

References 25 publications

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“…This coupling may take various forms, such as a basic gearbox, a pulley-belt assembly, a sprocket-chain arrangement, or a singular axle. The parallel hybrid drivetrain demonstrates several noteworthy advantages [31,[64][65][66][67]. 1.…”

Section: Parallel Hevmentioning

confidence: 99%

Review of Hybrid Energy Storage Systems for Hybrid Electric Vehicles

Urooj,

Nasir

2024

Preprint

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Energy storage systems play a crucial role in the overall performance of hybrid electric vehicles. Therefore, the state of the art in energy storage systems for hybrid electric vehicles has been discussed in this paper along with appropriate background information for facilitating future research in this domain. Specifically, we have compared the key parameters such as cost, power density, energy density, cycle life, and response time for various energy storage systems. For the energy storage systems employing ultra capacitors, we have presented the characteristics such as cell voltage, cycle life, power density and energy density. Furthermore, we have discussed and evaluated the interconnection topologies for the existing energy storage systems. We have also discussed the hybrid battery-flywheel energy storage system as well as the mathematical modeling of the battery-ultracapacitor energy storage system. Toward the end, we have discussed energy efficient powertrain for hybrid electric vehicles.

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Section: Parallel Hevmentioning

confidence: 99%

Review of Hybrid Energy Storage Systems for Hybrid Electric Vehicles

Urooj,

Nasir

2024

Preprint

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“…As for rule-based optimization algorithm, the rule-based method was employed to define the mode switching border. The charge-depleting mode (CD) of the rule-based energy strategy was then replaced with an instantaneous optimization method to discover the real-time optimal solution [17]. As for agriculture machines, the tractor operated approximately at a known speed except with load fluctuations, so the charge-sustaining of rule-based could be trial in a specific driving cycle [18].…”

Section: Introductionmentioning

confidence: 99%

Optimal energy management strategy for dual-power coupling tractor based on the adaptive control technology

Dou,

Wei,

et al. 2023

PLoS ONE

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Hybrid tractors (HT) are regarded as the efficient agricultural machine due to their energy conservation performance and faster torque response to deal with load fluctuations. However, the strategy to allocate the battery and fuel energy for demand power should be discussed. In this paper, an on-line management strategy of the HT is proposed to optimize the energy consumption of engine and motor and to reduce torque ripple for power units. A new architecture for replacing power shift and continuously variable transmission technology is proposed. Then, the modified equivalent consumption minimization strategy (ECMS) is used to optimize the torque distribution in which the equivalent factor is further calculated for the real-time process. Besides, the modification of ECMS in variable working conditions can effectively analyse the torque distribution between the motor and engine. The numerical test is implemented that the effectiveness of the proposed energy strategy is validated in plowing conditions. The consequences indicated that the proposed power distribution strategy can adaptively allocate the torque demand according to the fluctuation load. Comparing with the traditional rule-based strategy, the proposed strategy can reduce 6.2% of the energy, and decrease torque ripple with the proposed tractor architecture.

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An improved MPSP‐based path‐following control method for USV with input disturbances

Li,

Hu,

Dong

et al. 2024

Optim Control Appl Methods

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This study proposes an improved model predictive static programming (MPSP) based path‐following control method for unmanned surface vessel (USV) subject to input disturbances. The method addresses the challenges of accurate USV dynamics modeling, unpredictable maritime environments, and limited power and energy systems. A trajectory generator is designed to construct smooth reference trajectories, and the MPSP algorithm is adapted to handle path‐following problems while considering state and input constraints. An event‐triggered mechanism is introduced to reduce computational burden and conserve energy. Comparative simulations demonstrate the superiority of the proposed method over open‐loop tracking and the original MPSP approach in terms of tracking accuracy, disturbance rejection, and overall control performance. The improved MPSP‐based control method offers a robust and efficient solution for USV path‐following tasks, ensuring accurate tracking even in the presence of environmental disturbances and system uncertainties.

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Energy Management of a Parallel Hybrid Electric Vehicle using Model Predictive Static Programming

Cited by 15 publications

References 25 publications

Review of Hybrid Energy Storage Systems for Hybrid Electric Vehicles

Review of Hybrid Energy Storage Systems for Hybrid Electric Vehicles

Optimal energy management strategy for dual-power coupling tractor based on the adaptive control technology

An improved MPSP‐based path‐following control method for USV with input disturbances

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