Development of a Heavy Truck Vehicle Dynamics Model using Trucksim and Model Based Design of ABS and ESC Controllers in Simulink
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| Language: | English |
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The Ohio State University / OhioLINK
2013
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| Online Access: | http://rave.ohiolink.edu/etdc/view?acc_num=osu1364407532 |
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ndltd-OhioLink-oai-etd.ohiolink.edu-osu1364407532 |
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oai_dc |
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NDLTD |
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English |
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Automotive Engineering Mechanical Engineering Heavy truck vehicle dynamics Hardware-in-the-loop Software-in-the-loop SIL HIL ABS ESC TruckSim dSPACE ControlDesk Electronic stability control Anti lock braking Matlab Simulink Control CAN SAE J1939 |
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Automotive Engineering Mechanical Engineering Heavy truck vehicle dynamics Hardware-in-the-loop Software-in-the-loop SIL HIL ABS ESC TruckSim dSPACE ControlDesk Electronic stability control Anti lock braking Matlab Simulink Control CAN SAE J1939 Rao, Shreesha Yogish Development of a Heavy Truck Vehicle Dynamics Model using Trucksim and Model Based Design of ABS and ESC Controllers in Simulink |
| author |
Rao, Shreesha Yogish |
| author_facet |
Rao, Shreesha Yogish |
| author_sort |
Rao, Shreesha Yogish |
| title |
Development of a Heavy Truck Vehicle Dynamics Model using Trucksim and Model Based Design of ABS and ESC Controllers in Simulink |
| title_short |
Development of a Heavy Truck Vehicle Dynamics Model using Trucksim and Model Based Design of ABS and ESC Controllers in Simulink |
| title_full |
Development of a Heavy Truck Vehicle Dynamics Model using Trucksim and Model Based Design of ABS and ESC Controllers in Simulink |
| title_fullStr |
Development of a Heavy Truck Vehicle Dynamics Model using Trucksim and Model Based Design of ABS and ESC Controllers in Simulink |
| title_full_unstemmed |
Development of a Heavy Truck Vehicle Dynamics Model using Trucksim and Model Based Design of ABS and ESC Controllers in Simulink |
| title_sort |
development of a heavy truck vehicle dynamics model using trucksim and model based design of abs and esc controllers in simulink |
| publisher |
The Ohio State University / OhioLINK |
| publishDate |
2013 |
| url |
http://rave.ohiolink.edu/etdc/view?acc_num=osu1364407532 |
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AT raoshreeshayogish developmentofaheavytruckvehicledynamicsmodelusingtrucksimandmodelbaseddesignofabsandesccontrollersinsimulink |
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1719418776807538688 |
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ndltd-OhioLink-oai-etd.ohiolink.edu-osu13644075322021-08-03T05:21:10Z Development of a Heavy Truck Vehicle Dynamics Model using Trucksim and Model Based Design of ABS and ESC Controllers in Simulink Rao, Shreesha Yogish Automotive Engineering Mechanical Engineering Heavy truck vehicle dynamics Hardware-in-the-loop Software-in-the-loop SIL HIL ABS ESC TruckSim dSPACE ControlDesk Electronic stability control Anti lock braking Matlab Simulink Control CAN SAE J1939 The purpose of this thesis is to develop a vehicle dynamics model of a 6 X 4 cab-over tractor and a 2-axle semitrailer combination and a model-based design of ABS and ESC controllers. In addition to this, a Hardware-in-the-Loop (HIL) simulation of an Anti-lock Braking System (ABS) for a heavy truck was performed using dSPACE. TruckSim, developed by Mechanical Simulation Corporation (MSC), was used to model the vehicle dynamics. The tractor was equipped with disc brakes and the trailer was equipped with drum brakes. Model validation was by performing various dynamic maneuvers like J-turn, double lane change, decreasing radius curve test, high dynamic steer input and constant radius test with increasing speed. The model was validated in all three loading conditions: Bobtail or solo tractor, low CG trailer and high CG trailer condition. The vehicle responses obtained from TruckSim were compared against the experimental field test data obtained from the Heavy Truck Manufacturer (HTM). A hardware-in-the-loop (HIL) simulation of a heavy truck ABS system was setup in order to better understand the ABS control strategy and various activation thresholds involved. The test bench consists of six (6) brake chambers, ABS modulator valves, ABS electronic control unit from a commercial supplier, two air reservoirs, wheel speed sensors and pressure sensors for measuring the individual brake chamber pressures. dSPACE midsize was used to interface the vehicle model in TruckSim with the hardware components in the physical realm. The simulator converts the digital signals from TruckSim such as lateral acceleration, yaw rate and tractor speed into suitable analog signals which serve as inputs to the control module. For this simulation, the wheel speed signals coming from TruckSim were converted into an analog signal of sinusoidal form whose frequency is proportional to the wheel spin rate. TruckSim along with the hardware components thus forms a closed-loop system. The algorithm in the control module calculates the angular acceleration of the wheels from the wheel speed signals and rolling radius of tire and compares it with various thresholds. On encountering the thresholds, the control module energizes the solenoid valves in the ABS modulator to build, dump or hold the pressure in the brake chamber accordingly, thus preventing wheel lockup. The HIL simulation results were validated with the field test data by performing straight ahead braking tests on various friction surfaces and at different speeds. The tractor was tested in the laden and unladen condition since no trailer was connected. All the tractor axles were equipped with drum brakes for the ABS testing. By using the animation option in TruckSim, one can observe the vehicle motion in real-time under the action of the ABS controller.In addition to the HIL simulation, a Software-in-the-Loop (SIL) simulation was also performed wherein control algorithms for the Anti-lock braking system (ABS) and Electronic Stability Control (ESC) were developed in Simulink. An ESC system functions in two modes: Roll Stability Control (RSC) and Yaw Stability Control (YSC). The ESC control system model developed in this thesis deals with the roll stability mode. The roll stability control senses the lateral acceleration of the tractor-trailer combination and if it exceeds a certain critical threshold value, undertakes corrective measures by applying individual brakes or reducing the engine torque. The yaw stability control senses the yaw rate of the combination and calculates the vehicle slip rate and body slip angle. If the body slip angle and vehicle slip rate exceed a certain threshold, the yaw stability control applies differential braking at the steer axle or drive axle depending upon whether the combination is understeering or oversteering. This model is complemented by an ABS control module which modulates the brake pressure generated by the ESC module in order to prevent wheel lockup.The ABS model works on build-hold-dump methodology and was developed after doing a detailed analysis of the HIL simulation data. It is based on the calculation of the wheel angular acceleration and uses a first-order transfer function with suitable time constant to emulate the dynamic characteristics of an actual ABS pressure modulator valve and brake chamber. The pressure gradient and pressure build-up and release time constants were found out from the static pressure test data of a single brake chamber provided by HTM and also from the HIL simulation results. The tractor used for the field tests has a 4s4m ABS configuration and S-Cam drum brakes on all the axles and hence the ABS model in Simulink was developed to suit the same configuration. The TruckSim model was then integrated with the ABS Simulink model using S-function in Simulink. Straight ahead braking tests were performed to validate the ABS model with the field test data. The tests were performed on various friction surfaces such as homogeneous low coefficient of friction (µ), homogeneous high µ, split µ and jump µ. Brake chamber pressures, wheel slip ratios, wheel speeds, vehicle speed, stopping time and stopping distance were used as the performance metrics for the comparison.In addition to the ABS model, an ESC control system was created as a part of the SIL simulation process. Two vehicles models, namely a low CG combination and a high CG combination were utilized for this purpose. A mass estimation algorithm was developed which estimates the mass of the combination vehicle using the data which would normally be present on the CAN bus of an actual vehicle such as the engine torque, transmission gear status and vehicle speed. The estimated mass was then used to calculate the critical lateral acceleration threshold. A preview value for the lateral acceleration was calculated using a first order dynamic function which relates the lateral acceleration to the steering angle. This lateral acceleration value helps activate the RSC control ahead of time and hence keeps a check on the lateral acceleration. The measured lateral acceleration of the tractor was imported into the model from TruckSim using S-function. When the critical lateral acceleration is exceeded by the measured or the preview lateral acceleration, engine and brake control interventions are induced. The brake pressure decided by the RSC ultimately goes through an ABS system which prevents wheel lockup. The ABS system that was created earlier was implemented in the ESC model. In addition to the 4s4m system for the tractor, a 2s2m ABS system for the flatbed trailer was created and implemented. For the ESC model, the tractor axles were equipped with disc brakes and trailer axles were equipped with drum brakes.The ESC model was then validated with the field test data by performing various dynamic maneuvers such as double lane change, J-Turn, follow cone path, high dynamic steer input and constant radius test with increasing speed on various friction surfaces and at different speeds. Predominantly, the testing was done on medium and high friction surfaces such as dry asphalt, wet asphalt and moist asphalt since the possibilities of a rollover condition are higher on these surfaces. The lateral acceleration, yaw rate, road wheel angle, vehicle speed, brake chamber pressures, engine control and brake control activation signals were used as validation metric for making the comparison. Roll angle, roll rate and hitch articulation angle were not used because of the absence of corresponding experimental data. The comparison shows that the ESC model functions similar to the commercial ESC controller that was mounted on the truck during the field tests. 2013-07-11 English text The Ohio State University / OhioLINK http://rave.ohiolink.edu/etdc/view?acc_num=osu1364407532 http://rave.ohiolink.edu/etdc/view?acc_num=osu1364407532 unrestricted This thesis or dissertation is protected by copyright: all rights reserved. It may not be copied or redistributed beyond the terms of applicable copyright laws. |