A Hybrid Vehicle Hardware-in-the-Loop System With Integrated Connectivity for Ehorizon Functions Validation

Brunelli, Lorenzo; Capancioni, Alessandro; Gonnella, Pierpaolo; Casadio, Rebecca; Brusa, Alessandro; Cavina, Nicolò; Caggiano, Michele

doi:10.1109/tvt.2021.3073807

Cited by 9 publications

(3 citation statements)

References 19 publications

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“…In summary, prevailing challenges for virtual validation and XIL frameworks are increasing complexity of rest vehicle and environment simulation, optimised trade-offs between accuracy and computational power, and influences from global vehicle development. The first topic becomes manifest in connectivity (vehicle-to-vehicle or V2V,V2X) of the DUT and related control units which must be reproduced for adequate XIL validation [29,51,73,120,143,156,158]. Szalay considers a digitalised test environment, real-time localisation, low-latency communication (5G), and controllable scene objects as crucial components for an automated V2X virtual validation [156, pp.…”

Section: A a Summary Of X-in-the-loop Approaches To Datementioning

confidence: 99%

Methods for Virtual Validation of Automotive Powertrain Systems in Terms of Vehicle Drivability—A Systematic Literature Review

2023

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For the last two decades, an extensive transition in automotive X-in-the-loop activities from isolated electronic control units to real-time related, geographically distributed validation tasks has occurred. Benefits are strengthening frontloading, enabling concurrent engineering and reducing prototypes and testing efforts. As a downside, comprehensive system understanding and adequate simulation models must be provided. New technological trends like software-over-the-air-updates denote a continuous validation process even after the start of production. The present review focuses on the virtual validation of vehicle longitudinal dynamics. This exemplary field of application receives more and more attention as electrification of the vehicle powertrain accelerates, and this property directly influences the vehicle DNA. A systematic review process based on the PRISMA workflow has been conducted, focusing on drivabilityrelated powertrain applications. The investigation reveals the following trends: First, increasing complexity of virtualisation methods and models for validation activities influenced by vehicle-to-everything and geographically distributed development. Second, missing standards for virtual validation and proof of representativeness for combined real-virtual testing. In addition, many studies only contemplate the advantages of hardware-in-the-loop-driven development, disregarding crucial limitations and risks for such approaches. In conclusion, there is no longer the question of whether to validate virtually but how to comprehensible realise virtual validation.

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Section: A a Summary Of X-in-the-loop Approaches To Datementioning

confidence: 99%

Methods for Virtual Validation of Automotive Powertrain Systems in Terms of Vehicle Drivability—A Systematic Literature Review

2023

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“…By modeling and analyzing the power flow of each energy component in a hybrid electric system, the energy flow of a hybrid electric system can be controlled and optimized. An energy management strategy is responsible for controlling and optimizing the hybrid power system to achieve the goal of minimizing the equivalent fuel consumption [20]. In practice, this equivalent minimum fuel consumption model, combined with real-time vehicle data, can dynamically control and optimize the energy flow of a hybrid power system, which can realize optimal control.…”

Section: Building a Minimum Equivalent Fuel Consumption Modelmentioning

confidence: 99%

Energy Consumption Prediction and Control Algorithm for Hybrid Electric Vehicles Based on an Equivalent Minimum Fuel Consumption Model

Zhang

Tian

2023

Sustainability

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The development of hybrid technology can effectively solve the problems of the high pollution and energy consumption levels of automobiles. Therefore, an energy consumption prediction and control algorithm for hybrid vehicles based on a minimum equivalent fuel consumption model is proposed. The model’s battery power consumption is equivalent to the fuel consumption, and the sum of the engine fuel consumption and the battery equivalent fuel consumption is established as the objective function. By utilizing these factors, an innovative minimum equivalent fuel consumption model was constructed that could be used to measure the energy efficiency of hybrid vehicles. The longitudinal force result of braking force distribution control was obtained, as well as the energy consumption prediction structure of a hybrid electric vehicle. The rolling resistance, air resistance, and climbing resistance of the hybrid electric vehicles were calculated, and the energy consumption control algorithm for hybrid electric vehicles was constructed according to the calculation results. The experimental results indicated that under this research algorithm, the driving energy consumption of hybrid electric vehicles was relatively low and the energy consumption and energy efficiency measurements effectively met the actual demand, and the energy consumption prediction and control results were good.

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“…For the HiL setup, the entire vehicle is typically simulated, including all drive components and, if required, also the emissions. The ECU or HCU are coupled with the simulation as real components [69,70]. The highest virtualization level is used in the MiL or Software-inthe-Loop (SiL) setup.…”

Section: Virtual Test Benchesmentioning

confidence: 99%

Real Driving Emissions—Conception of a Data-Driven Calibration Methodology for Hybrid Powertrains Combining Statistical Analysis and Virtual Calibration Platforms

et al. 2021

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The combination of different propulsion and energy storage systems for hybrid vehicles is changing the focus in the field of powertrain calibration. Shorter time-to-market as well as stricter legal requirements regarding the validation of Real Driving Emissions (RDE) require the adaptation of current procedures and the implementation of new technologies in the powertrain development process. In order to achieve highest efficiencies and lowest pollutant emissions at the same time, the layout and calibration of the control strategies for the powertrain and the exhaust gas aftertreatment system must be precisely matched. An optimal operating strategy must take into account possible trade-offs in fuel consumption and emission levels, both under highly dynamic engine operation and under extended environmental operating conditions. To achieve this with a high degree of statistical certainty, the combination of advanced methods and the use of virtual test benches offers significant potential. An approach for such a combination is presented in this paper. Together with a Hardware-in-the-Loop (HiL) test bench, the novel methodology enables a targeted calibration process, specifically designed to address calibration challenges of hybridized powertrains. Virtual tests executed on a HiL test bench are used to efficiently generate data characterizing the behavior of the system under various conditions with a statistically based evaluation identifying white spots in measurement data, used for calibration and emission validation. In addition, critical sequences are identified in terms of emission intensity, fuel consumption or component conditions. Dedicated test scenarios are generated and applied on the HiL test bench, which take into account the state of the system and are adjusted depending on it. The example of one emission calibration use case is used to illustrate the benefits of using a HiL platform, which achieves approximately 20% reduction in calibration time by only showing differences of less than 2% for fuel consumption and emission levels compared to real vehicle tests.

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A Hybrid Vehicle Hardware-in-the-Loop System With Integrated Connectivity for Ehorizon Functions Validation

Abstract: Some rights reserved. The terms and conditions for the reuse of this version of the manuscript are specified in the publishing policy. For all terms of use and more information see the publisher's website.

Cited by 9 publications

References 19 publications

Methods for Virtual Validation of Automotive Powertrain Systems in Terms of Vehicle Drivability—A Systematic Literature Review

Methods for Virtual Validation of Automotive Powertrain Systems in Terms of Vehicle Drivability—A Systematic Literature Review

Energy Consumption Prediction and Control Algorithm for Hybrid Electric Vehicles Based on an Equivalent Minimum Fuel Consumption Model

Real Driving Emissions—Conception of a Data-Driven Calibration Methodology for Hybrid Powertrains Combining Statistical Analysis and Virtual Calibration Platforms

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