Modelling and Validation of An Electronic Wedge Brake System with Realistic Quarter Car Model for Anti-Lock Braking System Design
Bibliographic record
Abstract
Automotive vehicles are an integral part of almost every human being in every part of the world.The coming years will see increasing electrification of vehicles.The shift to electric vehicles is driven by the need of energy efficient and eco-friendly vehicles with low CO2 emission.Efficient use of the available energy requires the following [1]: Minimizing power losses in passive mode. Maximizing efficiency of components. Controlling power consumption via intelligent battery management and consumers.These factors motivate car companies to move towards drive-by-wire solutions in the future.With the advent of faster and more powerful computers and electronic components, the shift from mechanical systems to mechatronic systems is becoming reality.Mechatronic systems provide smarter, safer and more efficient solutions for vehicles.Drive-by-wire refers to automotive systems which replace the bulky and prone to failure mechanical systems like steering, braking, throttling, by mechatronic components.In drive-by-wire systems, the command signals to achieve the different tasks are carried by wires in form of electric signals and the command is passed on to mechatronic actuators.One such system is brake-by-wire (BBW), where the bulky brake fluids, pumps and pipes are replaced by electric wires, Abstract: With the advancement in battery and electronics technologies, soon Electric Vehicles (EV) will replace traditional vehicles as they are more efficient and environment friendly.This will require replacement of all mechanical systems in vehicles with their electrical counterparts.This study focuses on electromechanical brakes (EMB) as replacement of hydraulics brakes.Particularly a type of EMB known as Electronic Wedge Brake (EWB) which uses wedges to create self reinforcing braking force and consume less power than other EMBs.Detailed mathematical model of an EWB system is presented which provides braking force and torque to the disk brake.A Quarter Car Model (QCM) with realistic parameter values and aerodynamic deceleration is modelled to validate the EWB system.The system is validated for different road conditions and anti-lock braking system (ABS) is demonstrated for snowy road using a single PID controller.The results validate the brake and car model and a need for cascaded control strategy to implement ABS is established.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".