Automated Engine Calibration of Hybrid Electric Vehicles

Murgovski, Nikolce; Grahn, Markus; Johannesson, Lars; McKelvey, Tomas

doi:10.1109/tcst.2014.2360920

Cited by 11 publications

(5 citation statements)

References 54 publications

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“…The calibration is then released for validation. The evaluation is conducted based on a comparison with a theoretical optimum, e.g., determined by dynamic programming [41,42], and with validation in a prototype vehicle. In the current state, final approval of the calibration for homologation in accordance with legal requirements can only be obtained by validation in the vehicle [43].…”

Section: Methodology For Virtual Calibration Of Hybrid Electric Vehiclesmentioning

confidence: 99%

Virtual Multi-Criterial Calibration of Operating Strategies for Hybrid-Electric Powertrains

Düzgün,

Dorscheidt,

Krysmon

et al. 2023

Vehicles

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In hybrid vehicle development, the operating strategy has a decisive role in meeting the development goals, such as compliance with emission standards and high energy efficiency. A considerable number of interactions and cross-influences on other topics, such as emissions, on-board diagnostics, or drivability, must be considered during the calibration process. In this context, the given time constraints pose further challenges. To overcome these, approaches for virtualization of the calibration process are an effective measure. For this purpose, in the current study, a real engine control unit is embedded into a virtual simulation environment on so-called hardware-in-the-loop (HiL) testbenches, which allow virtual calibration and validation of the complete target vehicle. In this context, the paper presents a novel method for virtual calibration of operating strategies for hybrid-electric propulsion systems. This includes an innovative multi-criterial approach that considers the requirements of several development tasks, such as emission and OBD calibration. Measurement data for this optimization is generated on a HiL testbench setup tailored for the described methodology, including both the electrical setup and the simulation environment. To validate the selection of modeling approaches and the parametrization, the simulation environment is operated in open loop. The results of the open loop validation show promising behavior regarding the proposed use case. Finally, the presented methodology is evaluated regarding time and cost savings compared to a conventional approach.

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Section: Methodology For Virtual Calibration Of Hybrid Electric Vehiclesmentioning

confidence: 99%

Virtual Multi-Criterial Calibration of Operating Strategies for Hybrid-Electric Powertrains

Düzgün,

Dorscheidt,

Krysmon

et al. 2023

Vehicles

View full text Add to dashboard Cite

show abstract

“…Backward facing models assume that the vehicle follows the reference speed perfectly [55] and calculates the force required to do this using a model of the vehicle drag [56]. The tractive force and speed of the vehicle is then used to calculate the wheel speed and torque [57], and the information flows backwards through the model to calculate the required engine torque and speed which are then used to estimate the fuel consumption and emissions [58].…”

Section: Current Development In Vehicle Powertrain Modelsmentioning

confidence: 99%

Modelling and Co-simulation of hybrid vehicles: A thermal management perspective

Yuan

Fletcher

Ahmedov

et al. 2020

Applied Thermal Engineering

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“…Calibration of control parameters usually depends on the experience of designers [13], [14]. For complex systems, achieving optimal economy presents diffculty, and calibration efficiency is low.…”

Section: Control Strategies Of Hevs Are Usually Developed Based Onmentioning

confidence: 99%

Segemented Driving Cycle Based Optimization of Control Parameters for Power-Split Hybrid Electric Vehicle With Ultracapacitors

et al. 2019

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As energy storage device of hybrid electric vehicles (HEVs), ultracapacitors feature the advantages of higher power density and longer life cycle compared with batteries. However, when ultracapacitors of the same power level are used instead of batteries, fuel consumption becomes more sensitive to changes in control parameters as ultracapacitors store much less energy, and the state of charge (SOC) is powersensitive. In this paper, optimization of control parameters for a power-split HEV with ultracapacitors is addressed to achieve better fuel economy. First, a power-split HEV model and a corresponding control strategy are established under the MATLAB script environment for convenient analysis and application of an optimization algorithm. Second, focusing on the power-sensitive characteristic of the SOC, three key control parameters are determined, and their effects on fuel consumption are analyzed. Third, an improved particle swarm optimization (IPSO) algorithm is proposed to overcome the disadvantage of the PSO trapping into ''local optimum'' and improve optimization efficiency. To fully exploit the fuel-saving capability of the HEV, driving cycle segmentation is also considered. The IPSO is used to optimize three key control parameters under the segmented adapted world transient vehicle cycle. Finally, the optimal results are applied to hardware-in-the-loop test to verify the effectiveness of the proposed optimization method. Compared with the fuel consumption before optimization, the fuel saving rate reaches 9.20% in the urban section, 6.40% in the roadway section, and 5.40% in freeway section. INDEX TERMS Control strategy optimization, ultracapacitors, power-split hybrid system, improved particle swarm algorithm.

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Automated Engine Calibration of Hybrid Electric Vehicles

Cited by 11 publications

References 54 publications

Virtual Multi-Criterial Calibration of Operating Strategies for Hybrid-Electric Powertrains

Virtual Multi-Criterial Calibration of Operating Strategies for Hybrid-Electric Powertrains

Modelling and Co-simulation of hybrid vehicles: A thermal management perspective

Segemented Driving Cycle Based Optimization of Control Parameters for Power-Split Hybrid Electric Vehicle With Ultracapacitors

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