2023
13
1
0
4084
Effect of inlet flow condition on the thermal behavior of battery pack using a wavy cooling jacket
2
2
In recent years, the automotive industry has experienced a dramatic mutation in the develop ment of electric vehicles. One of the most important aspects of this type of vehicle is its thermal management. Among the various parts of an electric vehicle that are subjected to thermal management, the battery is of particular importance. Battery cell temperatures may exceed the allowable range due to continuous and high-pressure operation and various weather conditions, and this, in addition to performance, severely affects battery life. Therefore, the appropriate cooling system is essential. In this research, the most common methods of battery cooling are investigated. First, three-dimensional thermal analysis on the battery is performed using the computational fluid dynamics method in transient and steady-state phases. Then, the effect of changing the cooling flow rate on the maximum temperature of the battery cell as well as the temperature difference of the cells in the battery pack is investigated. The effect of changing inlet coolant temperature change on battery cell temperature distribution is also investigated. The results show that by increasing the flow rate from 0.5 to 1.2 liter per minute, the maximum temperature in the battery pack and the temperature difference between the cells decrease to 44.4 and 2.51 ° C, respectively. Also, by changing the temperature of the inlet coolant from 15 to 30 ° C, the maximum temperature in the battery pack increases up to 42.2 ° C and the temperature difference is negligible.
4026
4035
2023/03/5
1401/12/14
2022/12/9
1401/9/18
Ali
Modarresi
Ali
Modarresi
School of Automotive Engineering, Iran University of Science & Technology, Tehran, Iran
Saman
Samiezadeh
Saman
Samiezadeh
School of Automotive Engineering, Iran University of Science & Technology, Tehran, Iran
Ali
Qasemian
Ali
Qasemian
School of Automotive Engineering, Iran University of Science & Technology, Tehran, Iran
Electric Vehicles
Battery
Li-ion
Cooling
Computational Fluid Dynamics
[## ##]
Multi-Layer DC/DC Converter for Fuel Cell-Based Air Independent Propulsion System
2
2
One of the most important components of fuel cell power systems is the power conditioning subsystem. DC/DC converters play the leading role in the power conditioning subsystem and fuel cell hybridization with other electric power sources and storage. DC/DC converters control the load voltage and, in some cases, the fuel cell current, while current-controlled DC/DC converters control the loading level. Some advantages of designing converters in a multi-layer topology include reduced input current ripple and increased power density. Lower current-rating semiconductor devices can be used due to the current division among the layers and lower values of inductors and capacitors can be used due the lower input current and output voltage ripples, respectively. Furthermore, failure of one layer does not result in a complete system outage; the other layers can deliver a fraction of the nominal power. A fuel cell power system based on a 16 kW proton exchange membrane fuel cell stack and a multi-layer DC/DC boost converter is designed and implemented in this paper. The power system is intended for marine air-independent propulsion systems. The power system is modeled and analyzed using the MATLAB/Simulink software environment. The power system is implemented to verify the analysis and simulation results.
4036
4040
2023/03/52023/03/13
1401/12/22
2022/12/92023/03/19
1401/12/28
Hossein
Bagherian Farahabadi
Hossein
Bagherian Farahabadi
Northern Research Center for Science & Technology, Malek Ashtar University of Technology, Iran
bagherian@mut.ac.ir
Amirhossein
Pahnabi
Amirhossein
Pahnabi
Northern Research Center for Science & Technology, Malek Ashtar University of Technology, Iran
ahpahnabi@mut.ac.ir
Reza
Youneszadeh
Reza
Youneszadeh
Northern Research Center for Science & Technology, Malek Ashtar University of Technology, Iran
yuneszade@mut.ac.ir
Mohammad Ali
Alirezapouri
Mohammad Ali
Alirezapouri
Northern Research Center for Science & Technology, Malek Ashtar University of Technology, Iran
maa_pouri@mut.ac.ir
Mohammad
Rezaei Firuzjaei
Mohammad
Rezaei Firuzjaei
Northern Research Center for Science & Technology, Malek Ashtar University of Technology, Iran
mrezaei@mut.ac.ir
PEM fuel cell
Multi-layer
DC/DC Converter
Power system
Propulsion
[[1] S. Arumugam, E. L. Karthikeyan,P. Saikumar, A novel analysis of high frequency LLC converter for fuel cell systems, IEEE International Conference on Information Communication and Embedded Systems , (2013), pp. 913-918.##[2] N. Videau, G. Fontes, D. Flumian,G. Gateau, T. Meynard, J. L. daSilva, O. Verdu, High ratio non-isolated DC–DC converter for hydrogen battery using a 50kW PEM fuel cells, Fuel cells Vol. 17, No. 3, (2017), pp.187-195##[3] A. Kolli, A. Gaillard, A. D. Bernardinis, O. Bethoux, D. Hissel, Z. Khatir, A review on DC/DC converter architectures for power fuel cell applications, Energy Conversion and Management. Vol. 105,(2015), pp.716-730##[4] C. Wu, J. Chen, C. Xu, Z. Liu Z, Real-time adaptive control of a fuel cell/battery hybrid power system with guaranteed stability, IEEE Transactions on Control Systems Technology. Vol. 25, No. 4, (2016), pp. 1394-1405##[5] V. Boscaino, R. Miceli, C. Buccella, C. Cecati, H. Latafat, K. Razi, Fuel cell power system with LLC resonant DC/DC converter, IEEE International Electric Vehicle Conference, (2014), pp. 1-6.##[6] P. Thounthong, P. Mungporn, D. Guilbert, N. Takorabet, S. Pierfederici, B. Nahid-Mobarakeh, Y. Hu, N. Bizon, Y. Hangfu, P. Kumam, Design and control of multiphase interleaved boost converter based on differentail flatness theory for PEM fuel cell multi-stack applications, International Journal of Electrical Power & Energy Systems, Vol. 124, (2021), p. 106346.## ##]
Impedance evaluation of Li-ion battery with different continuous mother wavelets: A comparative study
2
2
As electric vehicles become more popular, we need to keep improving the lithium-ion batteries that power them. Electrochemical impedance spectroscopy (EIS) is used based on a discrete random binary sequence (DRBS) to reduce excitation time in the low-frequency region and excite the input of the battery. In this paper, voltage and current signals are processed with wavelet transform for impedance evaluation. In using wavelet transform, choosing the most optimal mother wavelet is crucial for impedance evaluation since different mother wavelets can produce different results. We aim to compare three types of continuous Morse mother wavelet, continuous Morlet, and continuous lognormal wavelet, which are among the most important mother wavelets, to determine the best method for impedance evaluation. We used the dynamic time-warping algorithm to quantify the difference between the initial values obtained from standard laboratory equipment and the impedance evaluation through three different continuous wavelets. Our proposed method (lognormal wavelet) has the lowest difference (3.4086) from the initial values compared to the Morlet (3.5504), and Morse (3.5457) methods. As a result, our simulation shows that the lognormal wavelet transform is the best method for impedance evaluation compared to Morlet and Morse wavelets.
4041
4050
2023/03/52023/03/132023/04/5
1402/1/16
2022/12/92023/03/192023/03/19
1401/12/28
Mahdi
Khoorishandiz
Mahdi
Khoorishandiz
Iran University of Science and Technology
Abdollah
Amirkhani
Abdollah
Amirkhani
Iran University of Science and Technology
amirkhani@iust.ac.ir
discrete random binary sequence
continuous wavelet transform
lithium-ion battery
dynamic time warping
[## ##]
Elman and Jordan neural networks for prediction of transient thermal contact for engine exhaust valve
2
2
In this study, feedback neural networks namely Elman and Jordan are used for prediction of exhaust valve temperature for air cooled engines. Input-output data are extracted from an experimental setup including the valve mechanism of an air cooled engine. Inverse heat transfer problem applying the Adjoint problem is used to address the thermal flux through exhaust valve and seat. Elman and Jordan neural networks are used to predict the transient valve temperature using the experimental data. The results show that Elman and Jordan neural networks predicts well the transient exhaust valve temperature. However, Jordan neural network with training algorithm of Gradient Descent with Adaptive Learning Rate performs better with RMSE error of 16.3 for prediction of exhaust valve temperature.
4051
4061
2023/03/52023/03/132023/04/52023/03/25
1402/1/5
2022/12/92023/03/192023/03/192023/03/19
1401/12/28
Mohsen
Motahari-Nezhad
Mohsen
Motahari-Nezhad
Technical and Vocational University
mmotaharinezhad@tvu.ac.ir
Elman
Jordan
Feedback network
Exhaust valve
Air cooled engine
[[1] M. A. S. Mohamed Hassan, Z. Mohamad Razlan, S. Abu Bakar, M. Afendi Rojan, W. K. Wan Ahmad, Z. Ibrahim, A. Ishak, A., A. Abdul Rahman and M. R. Mohd Jamir, "Approach to enhance the heat transfer of valve seats through," Applied Thermal Engineering, vol. 202, no. 117870, pp. 1-19, 2022. ##[2] M. Cerdoun, S. Khalfallah, A. Beniaiche and C. Carcasci, "Investigations on the heat transfer within intake and exhaust valves at various engine speeds," International Journal of Heat and Mass Transfer, vol. 147, no. 119005, pp. 1-12, 2020. ##[3] M. H. Shojaefard, A. R. Noorpoor, D. A. Bozchaloe and M. Ghaffarpour, "Transient thermal analysis of engine exhaust valve," Numerical Heat Transfer, Part A, vol. 48, p. 627–644, 2005. ##[4] M. Cerdoun and C. G. A. Carcasci, "Analysis of unsteady heat transfer of internal combustion engines’ exhaust valves," International Journal of Engine Research, p. 1–18, 2017. ##[5] C. S. Prasad, M. Babu and S. Sachin Raj, "Thermal analysis on exhaust valve with thermal barrier material," International Research Journal of Automotive Technology (IRJAT), vol. 1, no. 6, pp. 18-32, 2018. ##[6] H. Abdollahi, S. . Shahraki and M. Motahari-Nezhad, "A review on the effects of different parameters on contact heat transfer," Thermophysics and Aeromechanics, vol. 24, no. 4, 2017. ##[7] M. H. Shojaeefard, V. K. Mousapour and M. S. Mazidi, "The investigation of the effect of contact frequency upon thermal contact conductance," International Journal of Automotive Engineering, vol. 4, no. 1, 2014. ##[8] M. Motahari-Nezhad and A. Rahi, "Sensitivity analysis of different parameters affecting thermal contact conductance," International Journal of Automotive Engineering, vol. 8, no. 4, p. 2908, 2018. ##[9] M. A. S. M. Hassan, A. B. Shahriman, Z. M. Razlan, N. S. Kamarrudin, W. K. N. Khairunizam, M. S. M. Hashim, A. Harun, I. Ibrahim, I. Azizul Aziz, Z. Ibrahim, M. K. Faizi, M. F. H. Rani, A. Rahman, M. F. H. M F H Rani, M. A. Rojan and R. Mura, "Engine performance analysis by studying heat transfer in the valve seat through steady-state thermal simulation," Journal of Physics: Conference Series, vol. 2129, pp. 1-6, 2021. ##[10] M. Motahari-Nezhad, M. H. Shojaeefard and S. Shahraki, "Studying the transient thermal contact conductance between the exhaust valve and its seat using the inverse method," International Journal of Thermophysics, vol. 37, no. 13, pp. 1-25, 2016. ##[11] M. A. S. M. Hassan, A. B. Shahriman, Z. M. Razlan, N. S. Kamarrudin, I. A. Aziz, W. Khairunizam, M. S. M. Hashim, A. Harun, I. Z. I Ibrahim, M. K. Faizi, M. F. H. Rani and R. Murali, "Engine performance enhancement by improving heat transfer in between exhaust valve and valve seat through CFD (transient thermal) simulation," AIP Conference Proceedings, vol. 2339, 2021. ##[12] M. A. R. S. Al-Baghdadi, S. S. Ahmed and N. A. Ghayadh, "Mechanical and thermal stresses analysis in diesel engine exhaust valve with and without thermal coating layer on valve face," International Journal Of Energy And Environment, vol. 7, no. 3, pp. 253-262, 2016. ##[13] M. Cerdoun, S. Khalfallah and C. Carcasci, "Investigations on the heat transfer within intake and exhaust valves at various engine speeds," International Journal of Heat and Mass Transfer, pp. 1-12, 2020. ##[14] R. S. Rao, K. H. Reddy and C. R. V. Kumar, "Simulation of composite Titanium Nitrite (TiN) coated Internal Combustion engine exhaust valve using ANSYS," International Journal of Recent Technology and Engineering (IJRTE), vol. 8, pp. 626-631, 2019. ##[15] B. Pavel and D. Ales, "The simulation calculation of temperatures on valve seats of combustion engine and its verification," Advanced Materials Research, vol. 1016, pp. 577-581, 2014. ##[16] M. Mohsen Motahari-Nezhad and M. S. Mazidi, "An adaptive neuro-fuzzy inference system (ANFIS) model for prediction of thermal contact conductance between exhaust valve and its seat," Applied Thermal Engineering, vol. 105, pp. 613-621, 2016. ##[17] S. Fathi, M. E. Yazdi and A. Adamian, "Comparison of neural networks and fuzzy system for estimation of heat transfer between contacting surfaces," The Journal of Advanced Design and Manufacturing Technology (ADMT), vol. 12, no. 2, pp. 91-101, 2019. ##[18] K. Goudarzi, A. Moosaei and M. Gharaati, "Applying artificial neural networks (ANN) to the estimation of thermal contact conductance in the exhaust valve of internal combustion engine," Applied Thermal Engineering, vol. 87, pp. 688-697, 2015. ##[19] Z. C. Lipton, J. Berkowitz and C. Elkan, "A critical review of recurrent neural networks for sequence learning," Computer Science, 2015.## ##]
Path Planning and Optimal Control for Autonomous Exit Parking
2
2
The primary purpose of each autonomous exit parking system is to facilitate the process of exiting the vehicle, emphasizing the comfort and safety of driving in the absence of almost any human effort. In this paper, the problem of exit parking for autonomous vehicles is addressed. A nonlinear kinematic model is presented based on the geometric relationship of the vehicle velocities, and a linear time-varying discrete-time model of the vehicle is obtained for utilizing the optimal control strategy. The proposed path planning algorithm is based on the minimization of a geometric cost function. This algorithm works for ample space exit parking in Single-Maneuver and tight spaces in Multi-Maneuver exit parking. Finally, an optimal discrete-time linear quadratic control approach is hired to minimize a quadratic cost function. To evaluate the performance of the proposed algorithm, the control system is simulated by MATLAB/Simulink software. The results show that the optimal control strategy is well able to design and follow the desired path in each of the exit parking maneuvers.
4062
4076
2023/03/52023/03/132023/04/52023/03/252023/02/25
1401/12/6
2022/12/92023/03/192023/03/192023/03/192023/04/3
1402/1/14
Mohammad
Yar-Ahmadi
Mohammad
Yar-Ahmadi
K.N.Toosi University of Technology
myarahmadi@email.kntu.ac.ir
Hamid
Rahmanei
Hamid
Rahmanei
K.N.Toosi University of Technology
hrahmanei@mail.kntu.ac.ir
Ali
Ghaffari
Ali
Ghaffari
K.N.Toosi University of Technology
ghaffari@kntu.ac.ir
Autonomous Vehicle
Exit Parking
Linear Quadratic Tracking
Linear Time-varying Model
Path Planning.
[[1] C. Katrakazas, M. Quddus, W. Chen, L. Deka., Real-time motion planning methods for autonomous on-road driving: State-of-the-art and future research directions, J. Transportation Research Part C: Emerging Technologies, Vol. 60, (2015), pp. 416–442.##[2] Z. Lv, L. Zhao, and Z. Liu, A path-planning algorithm for automatic parallel parking, IMCCC, China, (2013), pp. 474-478.##[3] X. Ji, J. Wang, Y. Zhao, Y. Liu, L. Zang & B. Li, Path planning and tracking for vehicle parallel parking based on preview BP neural network PID controller, Trans. Tianjin University, Vol. 21, (2015), pp. 199-208.##[4] Z. Liang, G. Zheng, and J. Li, Automatic parking path optimization based on Bezier curve fitting, ICAL, China, (2012), pp. 583–587.##[5] F. Gómez-Bravo, F. Cuesta, A. Ollero, and A. Viguria, Continuous curvature path generation based on β-spline curves for parking manoeuvres, J. Robotic Autonomous Systems, Vol. 56, No. 4, (2008), pp. 360–372.##[6] H. Vorobieva, S. Glaser, N. Minoiu-Enache, S. Mammar Automatic parallel parking in tiny spots: Path planning and control, IEEE Transactions Intelligent Transportation Systems, Vol. 16, No. 1, (2015), pp. 396–410.##[7] H. Rezaei Nedamani, P. Masnadi Khiabani, and S. Azadi, Intelligent parallel parking using adaptive neuro-fuzzy inference system based on fuzzy c-means clustering algorithm, SAE Technical Papers, (2017).##[8] B. Lee, Y. Wei, and I. Y. Guo, Automatic parking of self-driving car based on LiDAR, Int. Arch. Photo., Rem. Sens. Spat. Inf. Sci. - ISPRS Archives, Vol. 42, (2017), pp. 241–246.##[9] Z. Qin, X. Chen, M. Hu, L. Chen, J. Fan, A novel path planning methodology for automated valet parking based on directional graph search and geometry curve, J. Robotic Autonomous Systems,Vol. 132, (2020).##[10] L. Cai, H. Guan, H. L. Zhang, X. Jia, J. Zhan, “Multi-maneuver vertical parking path planning and control in a narrow space,” J. Autonomous Systems, Vol. 149, ( 2022).##[11] P. Zips, M. Böck, A. Kugi, Optimisation based path planning for car parking in narrow environments, J. Robotic Autonomous Systems, Vol. 79, (2016).##[12] W. Yang, L. Zheng, Y. Li, Y. Ren, and Y. Li, A trajectory planning and fuzzy control for autonomous intelligent parking system, SAE Technical Papers, (2017).##[13] E. Ballinas, O. Montiel, O. Castillo, Y. Rubio, and Aguilar, A., Automatic parallel parking algorithm for a car-like robot using fuzzy pd+i control, Engineering Letters, Vol. 26, No. 4, (2018), pp. 447-454.##[14] X. Du and K. K. Tan, Autonomous reverse parking system based on robust path generation and improved sliding mode control, IEEE Transactions on Intelligent Transportation Systems, Vol. 16, No. 3, (2015), pp. 1225–1237.##[15] H. Ye, H. Jiang, S. Ma, B. Tang, and L. Wahab, “Linear model predictive control of automatic parking path tracking with soft constraints,” Int. J. Advanced Robotic Systems, Vol. 16, No. 3, (2019) , pp. 1–13.##[16] C. Ma, F. Li, C. Liao, and L. Wang, Path following based on model predictive control for automatic parking system, SAE Technical Papers, (2017).##[17] A. Ghaffari, A. Khodayari, F. C. Samavati, Advanced control and dynamic systems. K.N.T.U Press, Tehran, Iran (2020). (In Persian)## ##]
Engine Saturation Effect on Consensus of Decentralized Bi-Directional Nonlinear Self-Driving Vehicle Convoys
2
2
In this paper, the consensus of second-order nonlinear self-driving vehicle convoys (SDVCs) is studied. We assume that each self-driving vehicle (SDV) communicates only with one front and one rear SDVs. Each SDV’s nonlinear dynamics consisting of the rolling resistance and the air drag force is a function of SDV’s speed and is investigated in SDVC’s modeling and consensus design. Since the speed is bounded, all vehicles’ nonlinearities are also bounded. Due to engine saturation of each SDV, the control input is limited. We involve this limitation by introducing the arctan(.) function to control protocol. The inter-SDV’s distances are assumed to be constant during motion. The distance tracking error associated with each SDV is defined as distance between it and the leading SDV. The error dynamics of the proposed SDVC is derived after applying the consensus law to each SDV. To prove the internal stability, the Lyapunov theorem is employed. We will prove that under this consensus algorithm, the SDVC will be internal stable. To validate the effectiveness of this method, a SDVC comprising a leading and 6 following SDVs will be studied. It will be verified that under the proposed consensus law, all the SDVs reach a unique consensus.
4077
4084
2023/03/52023/03/132023/04/52023/03/252023/02/252023/03/3
1401/12/12
2022/12/92023/03/192023/03/192023/03/192023/04/32023/04/3
1402/1/14
Hossein
Chehardoli
Hossein
Chehardoli
Department of Mechanical Engineering, Ayatollah Boroujerdi University
h.chehardoli@abru.ac.ir
Self-driving vehicle convoy (SDVC)
Engine saturation
Bi-directional
Lyapunov function
Second-order nonlinear SDVs
[[1] C. Bergenhem, S. Shladover, E. Coelingh, C. Englund, and S. Tsugawa, "Overview of platooning systems," in Proceedings of the 19th ITS World Congress, Oct 22-26, Vienna, Austria (2012), 2012. ##[2] H. Ge, R. Cheng, and L. Lei, "The theoretical analysis of the lattice hydrodynamic models for traffic flow theory," Physica A: Statistical Mechanics and its Applications, vol. 389, no. 14, pp. 2825-2834, 2010.##[3] S. Santini, A. Salvi, A. S. Valente, A. Pescapé, M. Segata, and R. L. Cigno, "A consensus-based approach for platooning with intervehicular communications and its validation in realistic scenarios," IEEE Transactions on Vehicular Technology, vol. 66, no. 3, pp. 1985-1999, 2016.##[4] L. D. Baskar, B. De Schutter, and H. Hellendoorn, "Optimal routing for automated highway systems," Transportation Research Part C: Emerging Technologies, vol. 30, pp. 1-22, 2013.##[5] W. Zhang, E. Jenelius, and H. Badia, "Efficiency of semi-autonomous and fully autonomous bus services in trunk-and-branches networks," Journal of Advanced Transportation, vol. 2019, 2019.##[6] C. Deng and G.-H. Yang, "Leaderless and leader-following consensus of linear multi-agent systems with distributed event-triggered estimators," Journal of the Franklin Institute, vol. 356, no. 1, pp. 309-333, 2019.##[7] Y. Zheng, Q. Zhao, J. Ma, and L. Wang, "Second-order consensus of hybrid multi-agent systems," Systems & Control Letters, vol. 125, pp. 51-58, 2019.##[8] P. Yang, Y. Ding, X. Hu, Z. Zhang, and Z. Wang, "Sliding mode fault-tolerant consensus control for heterogeneous multi-agent systems based on finite-time observer and controller," Transactions of the Institute of Measurement and Control, p. 01423312221150292, 2023.##[9] G. Guo, P. Li, and L.-Y. Hao, "Adaptive fault-tolerant control of platoons with guaranteed traffic flow stability," IEEE Transactions on Vehicular Technology, vol. 69, no. 7, pp. 6916-6927, 2020.##[10] J. Chen, H. Liang, J. Li, and Z. Lv, "Connected automated vehicle platoon control with input saturation and variable time headway strategy," IEEE Transactions on Intelligent Transportation Systems, vol. 22, no. 8, pp. 4929-4940, 2020.##[11] Y. Bian, Y. Zheng, W. Ren, S. E. Li, J. Wang, and K. Li, "Reducing time headway for platooning of connected vehicles via V2V communication," Transportation Research Part C: Emerging Technologies, vol. 102, pp. 87-105, 2019.##[12] X. Guo, J. Wang, F. Liao, and R. S. H. Teo, "Distributed adaptive integrated-sliding-mode controller synthesis for string stability of vehicle platoons," IEEE Transactions on Intelligent Transportation Systems, vol. 17, no. 9, pp. 2419-2429, 2016.##[13] P. Wijnbergen and B. Besselink, "Existence of decentralized controllers for vehicle platoons: On the role of spacing policies and available measurements," Systems & Control Letters, vol. 145, pp. 1-9, 2020.##[14] J. Wang, X. Luo, W. Wong, and X. Guan, "Specified-Time Vehicular Platoon Control With Flexible Safe Distance Constraint," IEEE Transactions on Vehicular Technology, vol. 68, no. 11, pp. 10489-10503, 2019, doi: 10.1109/TVT.2019.2939558.##[15] I. Herman, S. Knorn, and A. Ahlén, "Disturbance scaling in bidirectional vehicle platoons with different asymmetry in position and velocity coupling," Automatica, vol. 82, pp. 13-20, 2017.##[16] M. Di Bernardo, A. Salvi, and S. Santini, "Distributed consensus strategy for platooning of vehicles in the presence of time-varying heterogeneous communication delays," IEEE Transactions on Intelligent Transportation Systems, vol. 16, no. 1, pp. 102-112, 2014.##[17] J. Huang, Q. Huang, Y. Deng, and Y.-H. Chen, "Toward robust vehicle platooning with bounded spacing error," IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, vol. 36, no. 4, pp. 562-572, 2016.##[18] H. Chehardoli and A. Ghasemi, "Adaptive centralized/decentralized control and identification of 1-D heterogeneous vehicular platoons based on constant time headway policy," IEEE Transactions on Intelligent Transportation Systems, vol. 19, no. 10, pp. 3376-3386, 2018.##[19] W. Yue and G. Guo, "Guaranteed cost adaptive control of nonlinear platoons with actuator delay," Journal of dynamic systems, measurement, and control, vol. 134, no. 5, pp. 136-144, 2012.##[20] W.-J. Liu, H.-F. Ding, M.-F. Ge, and X.-Y. Yao, "Cooperative control for platoon generation of vehicle-to-vehicle networks: a hierarchical nonlinear MPC algorithm," Nonlinear Dynamics, vol. 108, no. 4, pp. 3561-3578, 2022.##[21] L.-Y. Hao, P. Li, and G. Guo, "String stability and flow stability for nonlinear vehicular platoons with actuator faults based on an improved quadratic spacing policy," Nonlinear Dynamics, vol. 102, pp. 2725-2738, 2020.##[22] Y. He, X. Tian, J. Shen, C. Yuan, and Y. Du, "Robust stabilization of longitudinal tracking for cooperative adaptive cruise control considering input saturation," Modern Physics Letters B, vol. 34, no. 35, p. 2050409, 2020.##[23] Z. Gao, Y. Zhang, and Q. Liu, "Adaptive finite‐time cooperative platoon control of connected vehicles under actuator saturation," Asian Journal of Control, vol. 24, no. 6, pp. 3552-3565, 2022.##[24] X.-G. Guo, J.-L. Wang, F. Liao, and R. S. H. Teo, "CNN-based distributed adaptive control for vehicle-following platoon with input saturation," IEEE Transactions on Intelligent Transportation Systems, vol. 19, no. 10, pp. 3121-3132, 2017.##[25] C. Pan, Y. Chen, Y. Liu, and I. Ali, "Adaptive resilient control for interconnected vehicular platoon with fault and saturation," IEEE Transactions on Intelligent Transportation Systems, vol. 23, no. 8, pp. 10210-10222, 2021.##[26] G. B. Thomas, M. D. Weir, and J. Hass, "Thomas' Calculus: Multivariable," 2010.## ##]