Design and Analysis of Electrical Braking Torque Limit Trajectory for Regenerative Braking in Electric Vehicles With PMSM Drive Systems

Choo, Kyoung-Min; Won, Chung-Yuen

doi:10.1109/tpel.2020.2994615

Cited by 35 publications

(14 citation statements)

References 10 publications

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“…This method can be applied at any speed as proposed in [17]. The maximum torque per ampere (MTPA) control is adopted as the preferred control method applied in driving the IPMSM in electric vehicle due to the high torque capability at low speed and wide speed range as reported in [18]. The significance of maximum torque per ampere (MTPA) control method is to trace the minimum current vector that gives the required torque and current which also provides the maximum constant torque as given in [19].…”

Section: Related Workmentioning

confidence: 99%

A comparative braking scheme in auto-electric drive systems with permanent magnet synchronous machine

Omeje

Eya

2022

IJAPE

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<span lang="EN-US">Permanent magnet synchronous machines (PMSMs) are gaining popularity due to renewable energy and the electrification of transportation. Permanent magnet synchronous machines are receiving interest because to their great dependability, low maintenance costs, and high-power density. This research compares surface mounted permanent magnet (SMPM) with interior permanent magnet (IPM) synchronous machines using MATLAB. Mathematical models and simulation analyses of two permanent magnet synchronous machines under regenerative braking are presented. Maximum regeneration power point (MRPP) and torque (MRPP-torque) for two machine types were simulated at variable electrical speed and q-axis current. Simulation results showed IPMSM produced more output power due to saliency than SMPM at varying speed and current with higher MRPP and MRPP-Torque. Simulation was used to compare the dynamic impacts of constant and variable braking torques on an auto-electric drive's speed and produced torque on a plain surface and a sloppy driving plane. 81.68% and 74.95% braking efficiency were measured on level ground and a sloppy plane, respectively. Simulations indicated that lithium-ion battery state of charge varied linearly with constant braking torque and exponentially with varying braking torque, reflecting efficiency values. All simulations were in MATLAB/Simulink 2014.</span>

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Section: Related Workmentioning

confidence: 99%

A comparative braking scheme in auto-electric drive systems with permanent magnet synchronous machine

Omeje

Eya

2022

IJAPE

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“…In Equation ( 5), the following notations are used: K t = 3 2 n p λ 0 -the torque constant; B is the viscos friction coefficient; J is the rotor inertia; n p is the number of pole pairs; T L is the load torque.…”

Section: Description Of the Mathematical Model Of The Pmsm And The Foc-type Strategymentioning

confidence: 99%

“…These motors have significant advantages, drawing the interest of researchers and industry for their use in many applications. PMSMs are widely used in low-power and medium-power applications such as computer peripherals, robotics, adjustable speed systems, electric vehicles, and heavy-duty systems such as aerospace technology [1][2][3].…”

Section: Introductionmentioning

confidence: 99%

Sensorless Control of PMSM Based on Backstepping-PSO-Type Controller and ESO-Type Observer Using Real-Time Hardware

Nicola

Nicola²,

Selişteanu

2021

Electronics

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In the case of using a Permanent Magnet Synchronous Motor (PMSM) linear model of limited-range parametric variations and of relatively low dynamic of the load torque, the Field Oriented Control (FOC) type strategy ensures good performance of the PMSM control. Therefore, when using a non-linear model of wide-range parametric variations and of high dynamic of the load torque, a backstepping-type controller is proposed, whose tuning parameters are optimized by using a Particle Swarm Optimization (PSO) method. By designing an Extended State Observer (ESO), which provides a good estimate of the PMSM rotor position and speed under uncertainty conditions and with a response time shorter than that of the backstepping-type controller, this observer can be incorporated into the PMSM sensorless control system. The superior performance of the proposed sensorless control system based on the backstepping-PSO-type controller and an ESO-type observer is demonstrated through numerical simulations. Given that the real-time implementation of the control algorithms and observers in an embedded system is a difficult task, consisting of several steps, it is presented after the numerical simulations, which can be assimilated into the Software-in-the-Loop (SIL) step, the Processor-in-the-Loop (PIL) intermediate step, and the Hardware-in-the-Loop (HIL) final step. A comparison between the backstepping-PSO-type controller and the PI-PSO-type controller is presented by means of the real-time implementation of these controllers and demonstrates the superiority of the backstepping-PSO-type controller.

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“…By reversing current i q , magnetic resistance is applied to the loading motor under the action of reverse drag, and the process of simulating the load torque and inertia torque can be approximated as braking of the loading motor. At this stage, braking is classified into two categories, namely energy feedback and energy consumption braking [19][20][21][22]. The experimental results revealed that when the loading motor enters the energy consumption braking state, the additional energy consumption causes the driver that is coupled directly with the loading motor to produce undervoltage because of the braking state.…”

Section: Introductionmentioning

confidence: 99%

A Dynamic Load Simulation Algorithm Based on an Inertia Simulation Predictive Model

Lin

Wang

et al. 2022

Applied Sciences

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In this study, an electric dynamic load simulation system (EDLSS) algorithm was proposed based on an inertia simulation predictive model to mitigate strong-coupling torque disturbance and load torque fluctuation caused by the change in the motion state of a bearing system. First, the inertia simulation model was proposed by combining the dynamic equations of both the EDLSS and the target system. The aforementioned inertia simulation model converted the conventional realisation method of the inertia simulation into the tracking of the motion characteristics for the target system under the same working conditions. Next, based on the aforementioned inertia simulation model while considering the strong-coupling torque effect and motor braking state disturbance as two influential factors, an inertia simulation predictive model and a load simulation algorithm were proposed. The predicted speed calculated by the predictive model was consistent with the dynamic characteristics of the target system under the same working conditions and input into the control loop. Based on the analysis of the braking state and power model of the permanent magnet synchronous motor, an energy feedback control method was proposed to improve EDLSS stability caused by the braking state of the loading motor. Finally, the experimental data revealed that the maximum speed fluctuation range of the loading motor was approximately 7.5, which was 84% lower than the range before the application of the aforementioned algorithm, which was about 46.8. Furthermore, the maximum range of the torque ripple was close to 1.5, which was 75% lower than before, which was roughly 6. All experimental data were consistent with simulation data.

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Design and Analysis of Electrical Braking Torque Limit Trajectory for Regenerative Braking in Electric Vehicles With PMSM Drive Systems

Cited by 35 publications

References 10 publications

A comparative braking scheme in auto-electric drive systems with permanent magnet synchronous machine

A comparative braking scheme in auto-electric drive systems with permanent magnet synchronous machine

Sensorless Control of PMSM Based on Backstepping-PSO-Type Controller and ESO-Type Observer Using Real-Time Hardware

A Dynamic Load Simulation Algorithm Based on an Inertia Simulation Predictive Model

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