The Experts below are selected from a list of 4848 Experts worldwide ranked by ideXlab platform
Mehdi Ferdowsi - One of the best experts on this subject based on the ideXlab platform.
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modeling and integration of electric vehicle regenerative and friction braking for motor dynamometer test bench emulation
IEEE Transactions on Vehicular Technology, 2016Co-Authors: Poria Fajri, Sangin Lee, Venkata Anand Kishore Prabhala, Mehdi FerdowsiAbstract:This paper provides a new approach for emulating electric vehicle (EV) braking performance on a motor/dynamometer test bench. The Brake Force distribution between regenerative braking and friction braking of both the front and rear axles are discussed in detail. A Brake controller is designed, which represents a very close model of an actual EV braking system and takes into account both regenerative and friction braking limitations. The proposed Brake controller is then integrated into the controller of an EV hardware-in-the-loop (HIL) test bench, and its performance is validated in real-time. The effect of adding the Brake model is further investigated by comparing the experimental HIL energy consumption results with those obtained from ADvanced VehIcle SimulatOR (ADVISOR).
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Modeling and Integration of Electric Vehicle Regenerative and Friction Braking for Motor/Dynamometer Test Bench Emulation
IEEE Transactions on Vehicular Technology, 2016Co-Authors: Poria Fajri, S.-Y. Soo-Young Lee, Venkata Anand Kishore Prabhala, Mehdi FerdowsiAbstract:This paper provides a new approach for emulating electric vehicle (EV) braking performance on a motor/dynamometer test bench. The Brake Force distribution between regenerative braking and friction braking of both the front and rear axles are discussed in detail. A Brake controller is designed, which represents a very close model of an actual EV braking system and takes into account both regenerative and friction braking limitations. The proposed Brake controller is then integrated into the controller of an EV hardware-in-the-loop (HIL) test bench, and its performance is validated in real-time. The effect of adding the Brake model is further investigated by comparing the experimental HIL energy consumption results with those obtained from ADvanced VehIcle SimulatOR (ADVISOR).
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Emulating electric vehicle regenerative and friction braking effect using a Hardware-in-the-Loop (HIL) motor/dynamometer test bench
IECON 2014 - 40th Annual Conference of the IEEE Industrial Electronics Society, 2014Co-Authors: Poria Fajri, Venkata Anand Kishore Prabhala, Mehdi Ferdowsi, Nima Lotfi, Pourya ShamsiAbstract:This paper provides a new approach for emulating electric vehicle (EV) braking performance on a motor/dynamometer test bench. The Brake Force distribution between regenerative braking and friction braking of both the front and rear axles are discussed in detail. A Brake controller is designed, which represents a very close model of an actual EV braking system and takes into account both regenerative and friction braking limitations. The proposed Brake controller is then integrated into the existing controller of an EV Hardware-in-the-Loop (HIL) test bench, and its performance is validated in real-time using the same experimental setup.
Poria Fajri - One of the best experts on this subject based on the ideXlab platform.
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modeling and integration of electric vehicle regenerative and friction braking for motor dynamometer test bench emulation
IEEE Transactions on Vehicular Technology, 2016Co-Authors: Poria Fajri, Sangin Lee, Venkata Anand Kishore Prabhala, Mehdi FerdowsiAbstract:This paper provides a new approach for emulating electric vehicle (EV) braking performance on a motor/dynamometer test bench. The Brake Force distribution between regenerative braking and friction braking of both the front and rear axles are discussed in detail. A Brake controller is designed, which represents a very close model of an actual EV braking system and takes into account both regenerative and friction braking limitations. The proposed Brake controller is then integrated into the controller of an EV hardware-in-the-loop (HIL) test bench, and its performance is validated in real-time. The effect of adding the Brake model is further investigated by comparing the experimental HIL energy consumption results with those obtained from ADvanced VehIcle SimulatOR (ADVISOR).
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Modeling and Integration of Electric Vehicle Regenerative and Friction Braking for Motor/Dynamometer Test Bench Emulation
IEEE Transactions on Vehicular Technology, 2016Co-Authors: Poria Fajri, S.-Y. Soo-Young Lee, Venkata Anand Kishore Prabhala, Mehdi FerdowsiAbstract:This paper provides a new approach for emulating electric vehicle (EV) braking performance on a motor/dynamometer test bench. The Brake Force distribution between regenerative braking and friction braking of both the front and rear axles are discussed in detail. A Brake controller is designed, which represents a very close model of an actual EV braking system and takes into account both regenerative and friction braking limitations. The proposed Brake controller is then integrated into the controller of an EV hardware-in-the-loop (HIL) test bench, and its performance is validated in real-time. The effect of adding the Brake model is further investigated by comparing the experimental HIL energy consumption results with those obtained from ADvanced VehIcle SimulatOR (ADVISOR).
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Emulating electric vehicle regenerative and friction braking effect using a Hardware-in-the-Loop (HIL) motor/dynamometer test bench
IECON 2014 - 40th Annual Conference of the IEEE Industrial Electronics Society, 2014Co-Authors: Poria Fajri, Venkata Anand Kishore Prabhala, Mehdi Ferdowsi, Nima Lotfi, Pourya ShamsiAbstract:This paper provides a new approach for emulating electric vehicle (EV) braking performance on a motor/dynamometer test bench. The Brake Force distribution between regenerative braking and friction braking of both the front and rear axles are discussed in detail. A Brake controller is designed, which represents a very close model of an actual EV braking system and takes into account both regenerative and friction braking limitations. The proposed Brake controller is then integrated into the existing controller of an EV Hardware-in-the-Loop (HIL) test bench, and its performance is validated in real-time using the same experimental setup.
Venkata Anand Kishore Prabhala - One of the best experts on this subject based on the ideXlab platform.
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modeling and integration of electric vehicle regenerative and friction braking for motor dynamometer test bench emulation
IEEE Transactions on Vehicular Technology, 2016Co-Authors: Poria Fajri, Sangin Lee, Venkata Anand Kishore Prabhala, Mehdi FerdowsiAbstract:This paper provides a new approach for emulating electric vehicle (EV) braking performance on a motor/dynamometer test bench. The Brake Force distribution between regenerative braking and friction braking of both the front and rear axles are discussed in detail. A Brake controller is designed, which represents a very close model of an actual EV braking system and takes into account both regenerative and friction braking limitations. The proposed Brake controller is then integrated into the controller of an EV hardware-in-the-loop (HIL) test bench, and its performance is validated in real-time. The effect of adding the Brake model is further investigated by comparing the experimental HIL energy consumption results with those obtained from ADvanced VehIcle SimulatOR (ADVISOR).
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Modeling and Integration of Electric Vehicle Regenerative and Friction Braking for Motor/Dynamometer Test Bench Emulation
IEEE Transactions on Vehicular Technology, 2016Co-Authors: Poria Fajri, S.-Y. Soo-Young Lee, Venkata Anand Kishore Prabhala, Mehdi FerdowsiAbstract:This paper provides a new approach for emulating electric vehicle (EV) braking performance on a motor/dynamometer test bench. The Brake Force distribution between regenerative braking and friction braking of both the front and rear axles are discussed in detail. A Brake controller is designed, which represents a very close model of an actual EV braking system and takes into account both regenerative and friction braking limitations. The proposed Brake controller is then integrated into the controller of an EV hardware-in-the-loop (HIL) test bench, and its performance is validated in real-time. The effect of adding the Brake model is further investigated by comparing the experimental HIL energy consumption results with those obtained from ADvanced VehIcle SimulatOR (ADVISOR).
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Emulating electric vehicle regenerative and friction braking effect using a Hardware-in-the-Loop (HIL) motor/dynamometer test bench
IECON 2014 - 40th Annual Conference of the IEEE Industrial Electronics Society, 2014Co-Authors: Poria Fajri, Venkata Anand Kishore Prabhala, Mehdi Ferdowsi, Nima Lotfi, Pourya ShamsiAbstract:This paper provides a new approach for emulating electric vehicle (EV) braking performance on a motor/dynamometer test bench. The Brake Force distribution between regenerative braking and friction braking of both the front and rear axles are discussed in detail. A Brake controller is designed, which represents a very close model of an actual EV braking system and takes into account both regenerative and friction braking limitations. The proposed Brake controller is then integrated into the existing controller of an EV Hardware-in-the-Loop (HIL) test bench, and its performance is validated in real-time using the same experimental setup.
Ingmar Ipach - One of the best experts on this subject based on the ideXlab platform.
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Brake response time is significantly impaired after total knee arthroplasty investigation of performing an emergency stop while driving a car
American Journal of Physical Medicine & Rehabilitation, 2015Co-Authors: Maurice Jordan, Ulfkrister Hofmann, Ina Rondak, Marco Gotze, Torsten Kluba, Ingmar IpachAbstract:Objective The objective of this study was to investigate whether total knee arthroplasty (TKA) impairs the ability to perform an emergency stop. Design An automatic transmission Brake simulator was developed to evaluate total Brake response time. A prospective repeated-measures design was used. Forty patients (20 left/20 right) were measured 8 days and 6, 12, and 52 wks after surgery. Results Eight days postoperative total Brake response time increased significantly by 30% in right TKA and insignificantly by 2% in left TKA. Brake Force significantly decreased by 35% in right TKA and by 25% in left TKA during this period. Baseline values were reached at week 12 in right TKA; the impairment of outcome measures, however, was no longer significant at week 6 compared with preoperative values. Total Brake response time and Brake Force in left TKA fell below baseline values at weeks 6 and 12. Brake Force in left TKA was the only outcome measure significantly impaired 8 days postoperatively. Conclusion This study highlights that categorical statements cannot be provided. This study's findings on automatic transmission driving suggest that right TKA patients may resume driving 6 wks postoperatively. Fitness to drive in left TKA is not fully recovered 8 days postoperatively. If testing is not available, patients should refrain from driving until they return from rehabilitation.
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Driving and emergency braking may be impaired after tibiotalar joint arthrodesis: conclusions after a case series
International Orthopaedics, 2015Co-Authors: Stefan Schwienbacher, Maurice Jordan, Ulfkrister Hofmann, Emin Aghayev, Antongiulio Marmotti, Christoph Röder, Ingmar IpachAbstract:Purpose To assess whether reaction time (RT) and movement time (MT), as the two components of the total Brake response time (TBRT) and Brake Force (BF) are different in patients with a foot joint arthrodesis in comparison to controls. Methods The study was a comparative case series in a driving simulator under realistic driving conditions. Mobile patients without a walker, ≥6 months after surgery who were driving a car and had no neurological co-morbidity, knee or hip joint prosthesis were included in the study. The selection criteria resulted in 12 patients with right tibiotalar joint arthrodesis (TTJA) and 12 patients with another right foot joint arthrodesis (OFJA), who were compared to 17 individuals without any ankle-joint pathology. For TBRT, an empirical safe driving threshold of 700 ms was used. The outcome measures were RT, MT, TBRT, BF and McGuire score. Results MT ( p = 0.034) and TBRT ( p = 0.026) were longer in TTJA patients in comparison with the controls. Also, more patients with TTJA than patients with OFJA and controls exceeded the safe driving threshold ( p = 0.028). The outcomes in OFJA patients and in controls were comparable. The McGuire score was similar between the TTJA and OFJA patients ( p = 0.26). Conclusions Significantly slower MT and TBRT, and significantly more patients exceeding the safe driving threshold, were observed after a tibiotalar-joint arthrodesis in comparison to the controls. Patients with OFJAs were not significantly different from the controls. Driving and emergency braking may be impaired after tibiotalar-joint arthrodesis.
Jounghee Lee - One of the best experts on this subject based on the ideXlab platform.
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Accurate Brake Torque Estimation With Adaptive Uncertainty Compensation Using a Brake Force Distribution Characteristic
IEEE Transactions on Vehicular Technology, 2017Co-Authors: Kyoungseok Han, Seibum B. Choi, Jonghyup Lee, Dongyoon Hyun, Jounghee LeeAbstract:This paper presents an adaptive individual Brake torque estimation method based on the characteristic of front-to-rear Brake Force distribution ratio. Most previous studies on tire Force estimation have assumed that Brake torques can be calculated out of Brake pressure and given fixed Brake gains. However, Brake gains are proportional to Brake pad friction coefficients, which are influenced significantly by operating or weather conditions. In this paper, it is assumed that the pad friction coefficients are the only uncertainties of the wheel dynamics model since they vary significantly according to the driving conditions. Furthermore, the vehicle specific Brake Force distribution is used to obtain the additional information. Thus, more practical aspects can be considered when calculating the Brake torque. The developed algorithm is verified through simulations and experiments using a production vehicle, and it confirms that the estimation performance is improved significantly compared with that without uncertainty compensation.