A signal hardware-in-the-loop model for electric vehicles

Vo-Duy, Thanh; Ta, Minh C.

doi:10.1186/s40648-016-0068-9

Cited by 17 publications

(11 citation statements)

References 12 publications

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“…In this work, the Magic Formula of Pacejka (MF) was used to compute the lateral force F yi acting in each tire, indexed by i, as function of wheel vertical force F zi , tire slip angle i and camber angle i . The MF can be expressed by the following equation [23]:…”

Section: Vehicle Dynamicmentioning

confidence: 99%

“…Evaluation of ESCs by MIL and HIL simulations has been presented in the literature. In [23] a platform with physical steering wheel, acceleration pedal, braking pedal and a computer running real-time simulation of the vehicle response to steering wheel, acceleration and breaking commands was proposed for HIL simulations. In [12], HIL was performed on a test bench consisting of a hydraulic braking system of four wheels, a Hydraulic Control Unit (HCU) to generate the pressure of wheel cylinder and a NI PXI system for real-time running of vehicle simulation and control software.…”

Section: Introductionmentioning

confidence: 99%

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Development and evaluation with MIL and HIL simulations of a LQR-based upper-level electronic stability control

Magalhães

Murilo

Lopes

2019

J Braz. Soc. Mech. Sci. Eng.

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This paper proposes an electronic stability control and shows MIL and HIL simulations performed for evaluation. Two designs are presented, one based on two-degrees-of-freedom linear model that includes side-slip and yaw motion and other based on three-degrees-of-freedom linear model that includes roll motion. Model-in-the-loop and Hardware-in-the-loop simulations were performed to test ESC on vehicle represented by a nonlinear model that considers lateral, yaw and roll motions and an intelligent driver model to generate the steering wheel command as driver reaction to vehicle motion in respect with desired path. It's found from simulations for double lane change maneuver that the proposed controller is effective in reducing of sideslipping, rolling and yaw rate errors, keeping the steering stable in scenarios where the driver loses control of the vehicle, even in presence of disturbances in vehicle response in relation with response predicted by linear model used for control design. Keywords Electronic stability control • Linear quadratic regulator • Hardware-in-the-loop • Vehicle steering dynamic List of symbols a Length from front axis to center of mass b Length from rear axis to center of mass l Vehicle total length from rear axis to front axis t f Front track width t r Rear track width h s Height of center of mass above rolling center h Height of center of mass m s Sprung mass I zz Yawing inertial moment I xx Rolling inertial moment I xz Inertial product related to yawing and rolling c f Front rolling damping coefficient c r Rear rolling damping coefficient k f Front rolling stiffness coefficient k r Rear rolling stiffness coefficient f ∕ Front steer-by-roll coefficient M u Extra yaw moment given as control signal I s Steering coefficient u Vehicle longitudinal speed v Vehicle lateral speed Yaw angle Roll angle f Steering angle of front wheels r Steering angle of rear wheels D Front steer angle due to the driver's steering wheel command F yi Lateral force generated by tire i Camber angle i Tire slip angle of wheel i Vehicle side-slip angle g Gravity acceleration C i Cornering stiffness of wheel i C i Camber stiffness K Camber gradient r ∕ Rear steer-by-roll coefficient Tire-road friction coefficient

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Section: Vehicle Dynamicmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Development and evaluation with MIL and HIL simulations of a LQR-based upper-level electronic stability control

Magalhães

Murilo

Lopes

2019

J Braz. Soc. Mech. Sci. Eng.

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“…The vehicle dynamic model can obtain the actual speed of the vehicle on the basis of the longitudinal dynamic equation, and then send the speed to the driver module to form a closed-loop test. According to the relevant knowledge of automobile theory, traction (F t ) is the sum of rolling resistance (F f ), air resistance (F w ), slope resistance (F i ) and acceleration resistance (F j ), as shown in Equation (8). And the vehicle speed can be obtained by expanding this equation.…”

Section: The Design Of Vehicle Modelmentioning

confidence: 99%

“…In the test system, the vehicle model runs in real-time simulation environment, and the measurement signal is managed and controlled in the model. Besides that, VCU to be measured is in the form of hardware [8]. The specific features are integrated:…”

Section: System Designmentioning

confidence: 99%

Design of HIL Test System for VCU of Pure Electric Vehicle

Nie¹,

Wu²,

Liang³

2017

Proceedings of the 2017 2nd International Conference on Materials Science, Machinery and Energy Engineering (MSMEE 2017)

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Abstract. In order to achieve the test of function and strategy of pure electric car vehicle control unit(VCU) better, this paper designs a hardware-in-the-loop (HIL) test system for VCU based on NI-PXI platform. Firstly, expounding the principle of HIL testing technology and introducing the HIL test system plan based on demand analysis, then making sure the hardware which is used by system, and using it to build a vehicle model with MATLAB/Simulink successfully, finally running tests on the HIL testing system to demonstrate the political legitimacy and viability of the system.

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“…Although the developed model of this work only focuses on lateral behavior, the benefit of the real-time simulation system was fully exploited. Some other studies aimed to build HIL system in a signal level in order to validate vehicle control units in several applications, such as for motion control purpose [30,31], for motor control and power supply evaluation [32], or for ECU development [33]. These works have taken into account many hardware platforms, including DS2210 of dSPACE, NI-PXI and CompactRIO of National Instruments.…”

mentioning

confidence: 99%

Experimental Platform for Evaluation of On-Board Real-Time Motion Controllers for Electric Vehicles

Vo-Duy

Nguyễn

et al. 2020

Energies

Self Cite

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Electric vehicles are considered to be a greener and safer means of transport thanks to the distinguished advantages of electric motors. Studies on this object require experimental platforms for control validation purpose. Under the pressure of research, the development of these platforms must be reliable, safe, fast, and cost effective. To practically validate the control system, the controllers should be implemented in an on-board micro-controller platform; whereas, the vehicle model should be realized in a real-time emulator that behaves like the real vehicle. In this paper, we propose a signal hardware-in-the-loop simulation system for electric vehicles that are driven by four independent electric motors installed in wheels (in-wheel motor). The system is elaborately built on the basis of longitudinal, lateral, and yaw dynamics, as well as kinematic and position models, of which the characteristics are complete and comprehensive. The performance of the signal hardware-in-the-loop system is evaluated by various open-loop testing scenarios and by validation of a representative closed-loop optimal force distribution control. The proposed system can be applied for researches on active safety system of electric vehicles, including traction, braking control, force/torque distribution strategy, and electronic stability program.

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A signal hardware-in-the-loop model for electric vehicles

Cited by 17 publications

References 12 publications

Development and evaluation with MIL and HIL simulations of a LQR-based upper-level electronic stability control

Development and evaluation with MIL and HIL simulations of a LQR-based upper-level electronic stability control

Design of HIL Test System for VCU of Pure Electric Vehicle

Experimental Platform for Evaluation of On-Board Real-Time Motion Controllers for Electric Vehicles

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