HO CHI MINH CITY UNIVERSITY OF TECHNOLOGY AND EDUCATIONFACULTY FOR HIGH QUALITY TRAINING PROPOSAL ADAPTIVE CRUISE CONTROL DESIGN USING CARSIM DU THÀNH VINH Student ID: 20145020 VÕ NGỌC
OVERVIEW
Introduction
Since the introduction of vehicles, manufacturers have continuously integrated technologies to prevent collisions However, significant advancements began in the mid-1990s, enabling cars to intelligently assist drivers in maintaining safe distances from vehicles ahead.
The adaptive cruise control (ACC) system first emerged in Japan in the early 1990s, primarily alerting drivers to slower traffic without controlling the vehicle's throttle or brakes In contrast, Mercedes introduced the first true ACC system, known as Distronic, in 1999 with the S-Class limousine, which effectively managed both throttle and brakes to maintain a safe distance from the vehicle ahead.
Adaptive cruise control (ACC) is a technology that assists vehicles in maintaining a safe distance from other cars while adhering to speed limits By automatically adjusting the vehicle's speed, ACC enhances driving convenience and safety for drivers.
Adaptive cruise control is one of 20 terms used to describe its functions so that you might see adaptive cruise control as the following in advertisements and vehicle descriptions:
Fig 1.2 Road conditions and the activation of ACC system on car
Adaptive Cruise Control (ACC) utilizes advanced sensory technology, including cameras, lasers, and radar, to assess the proximity of vehicles and other objects on the road This capability positions ACC as a foundational element for the development of future automotive intelligence.
These sensory technologies allow the car to detect and warn the driver about potential forward collisions When this happens, red lights begin to flash, and the phrase
'brake now!' appears on the dashboard to help the driver slow down There might also be an audible warning.
Adaptive cruise control enhances driving safety and comfort by monitoring surrounding vehicles and objects, allowing drivers to maintain a consistent speed Drivers can customize settings such as the distance to the vehicle ahead and select driving modes like economical, sporty, or comfortable Additionally, factors like speed limits, road curvature, and accident data play a crucial role in determining the optimal speed automatically selected by the system.
Fig 1.3 The simulation of car when activate ACC system
Cruise control has evolved significantly since its inception, initially available only in luxury vehicles due to high production costs With the advent of affordable sensors, adaptive cruise control is now becoming a standard feature in modern cars Consequently, an increasing number of drivers are seeking to equip their vehicles with adaptive cruise control systems to enjoy its numerous benefits.
Fig 1.4 Structure of ACC System Controller [4]
Literature review
In this day and age, there are so many studies about Modelling and Simulating the Adaptive Cruise Control System
Our group conducted extensive research on various references both within and outside Vietnam, focusing particularly on Mr Do Van Dung's lecture on automatic control in cars based on CCS This lecture outlines the main components, including sensors, switches, and actuators, as well as the fundamental principles of control and the operation of CCS Recognizing that the basic knowledge of ACC is rooted in CCS, we chose this material for our study Mr Dung's lecture highlights the key features of CCS.
Mr Do Van Dung showcased the CCS on the TOYOTA CRESSIDA using functional switches, block diagrams, and wiring schematics, providing valuable insights into this system.
Fig 1.6 CCS wiring diagram on TOYOTA CRESSIDA
In 2007, over 50 million cars were produced globally, according to sources from Vietnam Maritime University, with production increasing by 5% annually This growth in the automotive market presents several negative implications that the industry must address.
Firstly, the internal combustion engine has become one of the major polluting contributors to our environment
Oil prices are rising annually due to the rapid depletion of oil reserves Adaptive Cruise Control (ACC) is an innovative technology found in many modern vehicles, designed to enhance car performance This system maintains a consistent vehicle speed despite external factors like wind or changing road conditions, while also ensuring a safe distance from the vehicle ahead.
This paper presents the results of simulations cruise control system based forward vehicle dynamics with Matlab Simulink.
Fig 1.7 Simulate Cruise Control System using PID
The simulation results demonstrated that PID controllers effectively meet system requirements by automatically adjusting the torque of the internal combustion engine This adjustment ensures that the car's traction is balanced with external resistance, allowing for the maintenance of a stable speed even when faced with changing resistance.
Last but not least, the manual also presents the results of simulations cruise control system based forward vehicle dynamics with Matlab Simulink The simulation results
PID controllers effectively meet system requirements by automatically adjusting the torque of internal combustion engines This ensures that the car's traction is balanced with external resistance, allowing for stable speed maintenance even when faced with changing resistance conditions.
This is part of research project: Research controlled fuel efficiency for vehicle using gasoline engine.
Numerous international studies have focused on the modeling and simulation of Adaptive Cruise Control (ACC) systems For instance, PhD Yun Chenjiang developed a mathematical function-based model for the ACC system, utilizing a linear quadratic regulator for its design In this approach, the Q and R parameters are adjusted over time based on real-time traffic conditions The phase-plant method imposes constraints on these parameters, while the coefficient descent method is employed to address the constrained optimization problem.
Meanwhile, Controller Design consists of:
- Data based controller design method is also introduced in this paper, where the time vary vehicle dynamic parameters are no longer considered
Q-function, which contains Markovian state and action penalty, is introduced to indicate the cost function According to current traffic states, Q-function is generalized and minimized by directly using least error method, whose stability is ensured by nonlinear regression theory Simulation is conducted and results show the advantages of using time varying parameter linear quadratic regulator over other controller discussed in this paper Vehicle tests are also conducted to ensure the feasibility and efficiency of the controller.
The research team contributed valuable insights into the ACC system, utilizing formal modeling methods to identify a significant logical flaw related to poor synchronization To address this issue, the paper introduces an innovative optimized modeling solution grounded in the synchronization theory of Petri nets, enhancing the calculation of synchronic distance Simulation results indicate a remarkable average reduction of 91.357% in token accumulation, showcasing the model's effectiveness in improving reliability and minimizing the risk of rear-end collisions.
A team of authors from Thailand has contributed to enhancing the Adaptive Cruise Control (ACC) System by focusing on speed characteristics and time headway Their review highlights significant improvements in vehicles, particularly the Mitsubishi Galant, which now includes advanced features that enhance performance compared to earlier models A key innovation of the updated ACC system is its capability to maintain an appropriate inter-vehicle gap, adjusting based on the speed of the leading vehicle and the time headway (THW).
The adaptive cruise control system enhances traditional throttle valve mechanisms by integrating a drive-by-wire system that utilizes a DC motor for precise throttle valve positioning through PD control with command compensation Additionally, the automatic braking system features a DC motor connected via steel cable transmission, enabling automatic adjustment of the brake pedal to the desired level through torque control This integration of brake and velocity control allows for seamless speed management.
The adaptive cruise control (ACC) system aims to achieve eight desired speeds quickly while minimizing jerk and steady-state error A micro switch on the brake pedal enables the driver to regain control at any moment The system relies on three key inputs: the speed of the leading vehicle from the electronic control unit (ECU), the time headway (THW) set by the driver, and the actual gap measured by a laser scanner By processing these inputs, the ACC calculates distance error and relative velocity, which serve as inputs for a fuzzy controller This controller generates the desired speed command to maintain an appropriate gap based on the leading vehicle's speed and the desired time headway Experimental evaluations demonstrate the ACC system's effective performance across various conditions.
In conclusion, after examining various references from Vietnam and abroad, our team has gained clarity on how to approach our proposed topic We have decided to utilize these citations to guide the implementation of our project Additionally, we will consider using more sources if the current materials prove insufficient.
The urgency of topic
The automotive industry has significantly advanced, introducing various driver assistance features that enhance safety and reduce driver fatigue These innovative technologies also promote energy efficiency and effectively address fuel consumption issues, ultimately helping users save money on fuel expenses.
The Adaptive Cruise Control (ACC) system, an advancement of the traditional Cruise Control System, utilizes cutting-edge sensor technology to enhance driving comfort and safety With ACC, drivers can relax their foot from the gas pedal during long journeys, reducing fatigue Additionally, this system helps prevent speeding, minimizing the risk of road accidents caused by driver error.
Thus, we decided to choose this topic to research and analyse the practical elements of Adaptive Cruise Control System base on Carsim and Matlab/ Simulink.
Objectives
Following the urgency of topic, we set our targets:
- Have deep knowledge about ACC System.
- Self-study Simulink and Carsim.
- Design a control algorithms ACC System of Mazda CX-5 2021 by Matlab/ Simulink.
- Simulate Work-mode and Case Studies of ACC System by Carsim.
- Optimize the speed of car based on the control parameters in different kind of roads or seasons.
- Estimate the simulate models and results using field test data of Mazda CX-5 2021.
- Analyze pros and cons of ACC System to innovate it later.
Topic Limitation
Others: Using Simulink and Carsim to model the ideas
Applications: In Vehicle Automatic Control Curriculum and other relative subjects
Expected Outcome
Research all of ACC’s System clearly and have a systematical knowledge to apply it into practical.
Get more knowledge with Powertrain and the convert of the real condition into simulation as well as do mathematics to find out the transfer function.
Design the controller of ACC by Simulink and model the system by Carsim.
Simulate the designed system by Carsim in different working conditions:
- Straight way - Up hill - down hill
- Slip - Wet - Rough (Pitching, Rolling, Bouncing and Yawing).
Collect the data (graph, figure, parameters …) about velocity, acceleration, speed,time, from the Simulation to analyze and explain the factors that effect the system.
Gantt Chart
Fig 1.9 The time line divide the responsibilities of team members
SYSTEM MODELING
Introduction
Systems modeling is an interdisciplinary approach that utilizes models to design and analyze systems across various fields, including business, IT development, and engineering In the fashion industry, mathematical models are essential for comprehending and managing complex systems These mathematical equations play a crucial role in connecting variables and systems, enabling effective control and optimization.
We have to follow the line:
Respectively, we apply the physical laws to linearize system and get a set of linear differential equations.
Last but not least, using Laplace transformation can help us achieve the results described the operation of system In conclusion, we all need the system modeling because:
- Understand the functionality of the system
- Prevent from destroying the experiment tools
- Save time and the financial for experiment
Dynamical System
A dynamical system in mathematics is defined by a function that illustrates how a point evolves over time within a given space, similar to a parametric curve Notable examples of dynamical systems include mathematical models for the oscillation of a clock pendulum, the movement of water through a pipe, the erratic motion of airborne particles, and the seasonal population of fish in a lake each spring.
In physics, a dynamical system refers to a particle or group of particles whose state changes over time, governed by differential equations that include time derivatives Many physical systems can be represented by first-order differential equations, such as \$\dot{x} = \frac{dx}{dt} = f(x(t), u(t), t)\$, where \$x(t)\$ is the state vector, \$f\$ is a non-linear function that provides the time derivative of \$x(t)\$, and \$u(t)\$ represents the vector of control inputs at time \$t\$.
The dynamics of most systems are approximately linear is x= ˙ Ax+ Bu (2-2)
State-space equation
Using state-space equation can convert the differential equation n-order (system description) into first-order differential equation described as following matrix: ˙ x (t )= Ax (t )+ Bu (t ) : state equation (2-3) y (t)=Cx(t )+ Du(t ) : output equation (2-4)
Consequently, state-space equation used in almost modern control theory.
Transfer function
Linear time-variant systems possess a crucial characteristic: when the input is sinusoidal, the output remains sinusoidal at the same frequency, albeit with varying magnitude and phase These variations in magnitude and phase, dependent on frequency, are referred to as the system's frequency response.
It is possible to convert a time domain system into frequency domain system base on Laplace transform, known as the transfer function.
The Laplace transform of time domain function f(t):
Transfer function is the ratio between the Laplace’s image of input and output signal and can be represent as algebraic equation:
Y ( s)=U (s) ×G ( s) (2-6) (output signal = input signal * transfer function) The transfer function from input U(s) and output Y(s) is:
Cruise Control System
Automatic cruise control is an essential feature in many modern vehicles, serving as an example of a feedback control system This technology enables drivers to maintain their desired speed without constant manual adjustments, allowing for a more relaxed driving experience It operates by measuring the vehicle's current speed, comparing it to the set reference speed, and automatically adjusting the throttle to ensure optimal performance.
Fig 2.2 Cruise Control System Modeling
In this case, we consider a simple model of the vehicle dynamics, shown in free- body-diagram (FBD) above, consists:
- Resistive force (bv) System equation of the CCS is considered as: m v ˙ +bv=u (2-8)
We can find the Modeled Object H(s) by Laplace transform according to the vehicle dynamic above: f (t) −bv (t)=ma
Model the Cruise Control System on Simulink
Fig 2.3 Blocks represent the Cruise Control without PID
Fig 2.4 Graphs represent the data of Cruise Control without PID
In the case without PID controller, it is clearly to realize that the line in graphs increase or decrease sharply and this phenomenon does not appear in practical.
Fig 2.5 Blocks represent the Cruise Control with PID
Fig 2.6 Graphs represent the data of Cruise Control with PID
The CCS with a PID controller demonstrates a smoother signal compared to the previous simulation, aligning more closely with the desired values and resembling real data more accurately.
Model the Adaptive Cruise Control System on Simulink
Fig 2.7 Block represent the Adaptive Cruise Control System
Fig 2.8 Active Cruise Controller block
EXPERIMENT AND RESULTS
Setup the technical parameters on Carsim
3.1.1 Set the specifications of car
Distance from center to front axle 1040 mm
In this simulation, we choose Mazda-CX5 2021 as the base model, then set all the parameters in the Simulated Test Specifications.
Fig 3.2 Set the Simulated Test Specifications
Fig 3.3 The parameters of Mazda-CX5 2021
Fig 3.5 Adjust the parameters inside the Procedure
We set the car running constantly at the velocity of 110 km/h, as the velocity of the highway, the simulation duration is 60s.
The car is equipped with the automatic transmission and has the path follower system
Fig 3.6 Set the Miscellaneous Data: 3D Road
Fig 3.7 Adjust the Geometry and Friction
We set the car run in the 4-land road with the coefficient of friction of 0.85 to avoid slipping.
3.1.4 Building the Adaptive Cruise Control Model
Fig 3.8 Set the Miscellaneous Data: Generic Group
Fig 3.9 Adjust the data inside the Generic Group
Fig 3.10 Adjust the target forward speed (km/h) of Lead car on each time (s)
Fig 3.11 Setup the Sensor detection - Radar
Fig 3.12 The following car uses radar to detect the lead car
Experiment - Simulate the Adaptive Cruise Control System on Carsim
Fig 3.13 The lead car and following car start to move
At this time, the following car is moving in CCS mode at 110 km/h
Fig 3.14 The following car detects the lead car and deaccelerates
Next, when the following car observes the ahead car in the range of radar about 50m, then the ACC system will be activated
Fig 3.15 The lead car continues to move and the following car keeps on moving
Finally, when the lead car speed up again, the following car will move continuously in CCS mode at 110km/h
Fig 3.16 The graphs of lead and following car used ACC system
CONCLUSION
Conclusion
This paper details the design of a controller and the simulation process of an Adaptive Cruise Control (ACC) System using Carsim, highlighting the rationale for selecting a PID controller to manage distance and velocity control The results achieved closely align with the anticipated requirements.
- Research ACC system clearly and have a systematical knowledge to apply it into practical
- Get more knowledge with Power train and the convert of the real condition into simulation as well as do mathematics to find out the transfer function
- Model the ACC system by Carsim:
+ The car can run constantly at the cruise control mode (follow the path)
+ The controller of ACC system works well (the car can adapt to the front vehicles)
Limitation
Though the report got the requirements as supposed at the expected outcome, there still has some limitations:
- Do not have enough time to design the ACC system on Simulink well
- The conflicts and crashes between data in Carsim prevent from simulating different kinds of roads
- Cannot estimate the level of saving fuel as well as money when the car activates Adaptive Cruise Control System
Nevertheless, this is only a simulation with the absolute conditions Compared to the actual conditions, there so many factors below that affect to the ACC:
Using cruise control on hilly or winding roads can be dangerous due to abrupt changes in vehicle speed caused by terrain and road conditions, making it unsuitable for such environments In densely populated areas like Vietnam, where roads are narrow and congested, cruise control is primarily limited to highways or railways These systems cannot respond to sudden traffic changes, requiring drivers to manually disable cruise control to maintain control of the vehicle in the presence of obstacles or hazards.
Cruise control systems depend on electronic components and sensors, making them vulnerable to malfunctions As a result, Adaptive Cruise Control (ACC) may struggle in adverse weather conditions like heavy rain, snow, or fog In these scenarios, the radar system integral to ACC can malfunction, leading to unpredictable vehicle behavior and potential safety hazards.
Development proposal
Upgrade the Adaptive Cruise Control System to educated tool in University
Add this technology into curriculum for students have a broaden knowledge about the development on Automotive
Experiment in practice and evaluate the overall of the system about saving fuel, money and its efficiency