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"Teknologi yang sedang digunakan untuk mengoptimalkan pengereman ini merupakan Anti Lock Braking System (ABS). Teknologi ini menggunakan referensi rasio slip secara longitudinal pada roda dimana variabel ini mempunyai pengaruh terhadap koefisen gesek yang menyebabkan gaya gesek antara ban dan jalan menjadi maksimal. Rasio slip merupakan fungsi perbandingan kecepatan kendaraan dengan kecepatan roda dikalikan dengan jar-jari roda. Pengukuran kecepatan longitudinal kendaraan secara konvensional menggunakan perkalian radius roda dengan kecepatan angular roda yang dapat secara mudah diukur dengan sensor encoder. Akan tetapi metode ini mempunyai kelemahan yaitu tidak validnya kecepatan longitudinal yang didapat ketika kendaraan tetap melaju tetapi roda mengalami keadaan terkunci saat pengereman terjadi. Maka dari itu diperlukan adanya estimasi terhadap variabel kecepatan longitudinal kendaraan agar perhitungan rasio slip dapat dilakukan. Estimasi dilakukan menggunakan observer Adaptive Kalman Filter (AKF). Pada algoritma adaptif yang diusulkan adalah dengan memodifikasi gain pada algoritma Kalman filter konvensional. Gain dimodifikasi berdasarkan keadaan dari roda kendaraan saat terjadinya rasio slip berlebih atau ban yang terkunci dimana data dari akselerometer digunakan sepenuhnya. Desain observer ini menggunakan persamaan pengukuran dari kecepatan kendaraan yang diukur dari roda kendaraan dan masukan yang merupakan data dari akselerometer. Dengan adanya kombinasi dari dua pengukuran ini dapat diperoleh hasil yang optimal dimana terdapat kelebihan dari masing-masing sensor yang mengkompensasi kelemahan dari masing-masing sensor tersebut. Simulasi percobaan dilakukan menggunakan model half car dengan pengendali Proportional Integral (PI) dan Model Predictive Control (MPC) pada kondisi jalan aspal basah dan kering. Hasil estimasi terbaik didapatkan pada percobaan pengereman pada aspal basah dengan nilai cost function 0.002015. ......The technology that being used to optimize the braking is an Anti-Lock Braking System (ABS). The technology uses a reference of longitudinal slip ratio on wheels in which these variables have an influence on the coefficient of friction that causes frictional forces between the tire and the road becomes maximum. This is because that slip ratio is a function of the longitudinal vehicle velocity that can not be measured directly. Measurement of longitudinal velocity of the vehicle using a conventional radius multiplication wheels with wheel angular velocity that can be easily measured by the encoder sensor. However, this method has the disadvantage that the invalidity of the longitudinal speed obtained when the vehicle may have run but the wheels are over slip or the current state of the wheels are locked due to braking occurs. Thus it is necessary to estimate the variable speed of the vehicle that the longitudinal slip ratio calculation can be done. Estimation was performed using Adaptive Kalman Filter (AKF) observer. In the proposed adaptive algorithm is to modify the gain on conventional Kalman Filter algorithm. Gain is modified based on the state of the vehicle when the wheels are over slip locked then data from the accelerometer is fully used. The observer design using equation measurements of measured vehicle speed from the wheels of the vehicle and input observer is the data from the accelerometer. With the combination of these two measurements can be obtained optimal results where the advantages of each of the sensors can compensate for the weaknesses of each of these sensors. The simulation of system use the half car model with Proportional Integral (PI) and Model Predictive Control (MPC) controller on dry and wet asphalt for road condition. The best result of estimation achieved by simulation on wet asphalt with cost function value 0.02105."

"Pengujian electronic control unit ECU secara langsung pada kendaraan roda empat memiliki beberapa isu diantaranya faktor keamanan dan biaya. Oleh karenanya, diajukan metode pengujian Hardware In the Loop Simulation HILS. Divais yang diuji yaitu ECU Antilock Braking System ABS, dimana algoritma kendali yang diajukan adalah Model Predictive Control MPC dan sebagai pembanding digunakan algoritma Hysterisis Control. Platform Hardware-In-the Loop HILS yang digunakan pada penelitian ini berbasis NI Labview CompactRIO 9081, sedangkan untuk ECU menggunakan Texas Instrument RM48. Keduanya dihubungkan oleh sistem Data Acquisition DAQ. Model dari kendaraan roda empat pada penelitian ini dihasilkan dari perangkat lunak Carsim, prosedur pengereman juga dapat disimulasikan dengan Carsim. Dari hasil yang diperoleh, pengereman dengan pengendali mampu memperpendek jarak pengereman dan juga menjaga steerability dari kendaraan tidak hilang dibandingkan dengan pengereman tanpa kendali ABS.

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Testing under development electronic control unit ECU directly to four wheeled vehicles have a number of issues, including safety and financial. Therefore, Hardware in the loop simulation HILS method has been proposed. Device under test is ECU for Antilock braking system ABS, wherein the proposed control algorithm was Model Predictive Control MPC and Hysterisis Control as a comparison. Platform for hardware in the loop simulation HILS were used in the research based on Labview NI CompactRIO 9081, while the ECU was using Texas Instrument RM48. Both of them were connected by Data Acquisition DAQ system. The model of four wheel vehicles resulted from Carsim Car Simulation. Not only model but also braking situation can be simulated by Carsim. From the result, controller able to shorten the braking distance and maintain steerabilitiy of vehicle compare to vehicle without ABS."

"This fundamental work explains in detail the driver assistance systems for active safety and driver assistance, considering both their structure and their function. These include the well-known standard systems such as Anti-lock braking system (ABS), Electronic Stability Control (ESC) or Adaptive Cruise Control (ACC). But it includes also new systems for protecting collisions protection, for changing the lane, or for convenient parking.The book aims at giving a complete picture focusing on the entire system. First, it describes the components which are necessary for assistance systems, such as sensors, actuators, mechatronic subsystems, and control elements. Then, it explains key features for the user-friendly design of human-machine interfaces between driver and assistance system. Finally, important characteristic features of driver assistance systems for particular vehicles are presented: Systems for commercial vehicles and motorcycles."