Review of Vehicle Active Safety Systems and Their Coordinated Control

Zixiang       Zhao; Xiaobin       Fan

doi:10.2174/2212797613999200604155414

Abstract

Background: It is obvious that the safety concern associated with a vehicle is greatly valued by all, whether it is now or in the future, the automobile safety issue is the hotspot and the focus of the research by experts and scholars. The continuous increase in car ownership brings convenience to people's life and also poses a threat to people's life and property. Vehicles’ active safety system is the hotspot of current research and development, which plays an important role in automobile safety. Firstly, the vehicle’s active safety technology and its development are introduced. Then, a review is carried out examining the Anti-Lock Brake System (ABS), the Electronic Brake force Distribution (EBD/CBC), the Brake Assist System (BAS/EBA/BA), the Traction Control System (TCS/ASR), the Vehicle Stability Control (VSC/ESP/DSC), etc. At present, there are many patents on the control of each subsystem, but few patents on the integrated control for the active safety of vehicles.

Objective: The main contents of this paper are as follows: the control strategies and methods of different active safety systems, the strategies to improve the stability of a vehicle control system and ensure the effectiveness of active safety system control. It provides a reference for the development of active safety control technology and patent.

Methods: Through the analysis of different control algorithms and control strategies of Anti-lock and braking force distribution systems, it is pointed out that the switching of EBD/ABS coordinated control strategy according to slip rate can make full use of slip rate and road adhesion coefficient to improve the safety of the system. For the BAS, the slip problem is solved through the combination of the Mechanical Assistant Braking System (MABS) and Electronic Braking Assistant (EBA) system by measuring the distance and the speed of the vehicle ahead. The optimal slip rate control is realized by different control algorithms and control strategies of the traction control system. It is pointed out that the adaptive fuzzy neural controller should be used to control the yaw angular velocity and centroid side angle of the Electronic Stability Program (ESP), which has a good effect on maintaining vehicle stability. A sliding mode variable structure controller combined with constant speed control and law control is used to control the yaw moment.

Results: Through the coordinated control strategy of EBD/ABS, the slip rate and road adhesion coefficient were fully utilized by switching according to the slip rate. The problem of the sliding slope was solved by MABS with EBA system. The ESP should use an adaptive fuzzy neural controller to control the yaw angular velocity and centroid side angle, and adopt the joint sliding mode variable structure controller which combines the ABS control and the yaw moment control. Through the optimal control theory, the coordinated control of each subsystem can significantly improve driving stability, riding comfort, fuel economy and so on.

Conclusion: This study adopts different control strategies and control algorithms for different active safety control systems and makes full use of the tire-road friction coefficient and slip ratio optimal slip ratio. These focus on accurate control of control variables such as yawing angular velocity, centroid side-slip angle, yawing moment and finally ensure the vehicle braking stability, robustness of the controller and the lateral stability of the vehicle.

Keywords: Active safety system, coordinated control, optimum slip ratio, road adhesion coefficient, sideslip angle of center of mass, transverse angular velocity, yaw moment.

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[1] 
Tan ZF, Liu YC. Analysis on the impact of human behavior on road traffic safety. Forestry Construction  2005; 1: 30-3.
[2] 
Wang M, Wang CJ. The present situation and analysis of traffic safety of vulnerable traffic participants in China. Road Traffic and Safety  2010; 10(4): 9-14.
[3] 
Zhang YB, Lu HP, Liu Q. China’s road traffic safety situation and countermeasures. Changsha Institute of Transportation  2006; 3: 58-62.
[4] 
Gasmi A, Boudali M-T, Orjuela R, Basset M. Multi-criteria stability combination for yaw stability control of autonomous vehicles. IFAC-Papers OnLine 2019.  52(5): 465-70.
[5] 
Ma X, Wong PK, Zhao J, Xie X. Cornering stability control for vehicles with active front steering system using T-S fuzzy based sliding mode control strategy. Mech Syst Signal Process  2019; 125(15): 347-64.
[6] 
Reina G, Messina A. Vehicle dynamics estimation via augmented extended Kalman Filtering. Measurement  2019; 133: 383-95.
[http://dx.doi.org/10.1016/j.measurement.2018.10.030] 
[7] 
Fors V. Olofsson, Björn, Nielsen L. Formulation and interpretation of optimal braking and steering patterns towards autonomous safety-critical manoeuvres. Veh Syst Dyn  2019; 57(8): 1206-23.
[http://dx.doi.org/10.1080/00423114.2018.1549331] 
[8] 
Hou G, Chen S, Chen F. Framework of simulation-based vehicle safety performance assessment of highway system under hazardous driving conditions. Transp Res, Part C Emerg Technol  2019; 105: 23-36.
[http://dx.doi.org/10.1016/j.trc.2019.05.035] 
[9] 
Lin F, Zhang Y, Zhao Y. Trajectory tracking of autonomous vehicle with the fusion of dyc and longitudinal-lateral control. Chin J Mech Eng  2019; 32(1): 1-16.
[http://dx.doi.org/10.1186/s10033-019-0327-9] 
[10] 
Zhang B, Zong C, Chen G. A novel integrated stability control based on differential braking and active steering for four-axle trucks. Chin J Mech Eng  2019; 32(1): 1-21.
[http://dx.doi.org/10.1186/s10033-019-0323-0] 
[11] 
Sherony R. Personalized active safety systems. US10315648 2019.
[12] 
Bai YX, Wei XY. Review of automobile active safety. World Automob  1996; 3: 2-4.
[13] 
Besnoin E, Leconte ARG. Tire sensor for a tire monitoring system. US10406866 2017.
[14] 
Sabri Y, Zimmerman SE, Si Y. Methods and systems for estimating road surface friction. US10131360 2018.
[15] 
Berntorp K, Di Cairano S. System and method for determining state of stiffness of tires of vehicle. US10011284 2018.
[16] 
Askeland JL. Estimating friction based on image data. US10275662 2019.
[17] 
Varnhagen S, Kuang ML. Vehicle tire saturation estimator. US10065636 2017.
[18] 
Jonasson M, Ohlsson N. Method and system for determining tireto- road friction in a vehicle. US20190389475 2019.
[19] 
Chen S-K, Litkouhi BB, Pylypchuk V. Method and apparatus for accelerometer based tire normal force estimation.US20190389473 2019.
[20] 
Capua A, Jodorkovsky M. Method to estimate tire-road friction, prior to safety systems engagement. US20190256103 2019.
[21] 
Mahabadi SAK, Hashemi E. Corner-based longitudinal speed estimation. US10040460 2019.
[22] 
Ma FL. Research and implementation of control algorithm of ABS logic gate of vehicle. PhD Dissertation, Chongqing University of Posts and Telecommunications, Chongqing, China, May, 2011.
[23] 
Chen QF. Research on the ABS simulation experiment of the driver in the ring car PhD Dissertation, Kunming University of science and technology, Kunming, China, April,  2014.
[24] 
Zheng WF, Liu GF. Development of ABS in China. Auto Electronics  2005; 11: 1-3.
[25] 
Tang JH. Simulation and implementation of vehicle anti-lock braking system. PhD Dissertation, Hunan Normal University, Changsha, China, June 2014.
[26] 
Jiang KR, Wang ZC. ABS technology of the car and its development trend. Indust Instrum Automat Dev  2006; 2: 73-5.
[27] 
Wang JG, Li YY. A vehicle ABS brake test stand which can be used for various tests. CN106198046 2016.
[28] 
Liu GR, Lu GF, Wang J, et al. Zou, S., Liu, T., Tao, W., Qiang, J. A hydraulic active braking system of vehicle and its control method. CN106379302 2017.
[29] 
Liu ZY, Wang Y, Zhang ZZ, Zhang ZY, Fu HW. A vehicle automatic emergency braking system based on ABS/ASR. CN106891874 2017.
[30] 
Kraft HJ, Leffler H. The Integrated brake and stability control system of the new BMW 850i. International Congress & Exposition, SAE International. Chicago, United States, February, 1990. 
[31] 
Shibahata Y, Shimada K, Tomari T. The improvement of vehicle maneuverability by direct yaw moment control. Proceedings of the International Symposium on Advanced Vehicle Control TRB Publications Yokohama, Japan September, 1992. 
[32] 
Zanten ATV, Gmbh RB. Evolution of electronic control systems
for improving the vehicle dynamic behavior. 6th International Symposium
on Advanced Vehicle Control (AVEC) & Springer Science.
Hiroshima, Japan, February, 2002 
[33] 
Leiler H. Consideration of lateral and longitudinal vehicle stability by function enhanced brake and stability control system. International Congress & Exposition, SAE International Chicago, United States, March, 1994. 
[34] 
Alberti V, Babbel E. Improved driving stability by active braking of the individual wheels. International Symposium on Advanced Vehicle Control & Journal of Economic Ref. Aachen, Germany. 1996.
[35] 
Zanten ATV, Rainer E, Klaus L, Georg P. VDC systems development and perspective. SAE Paper  1998; 28(12): 424-9.
[http://dx.doi.org/10.4271/980235] 
[36] 
Gu WL, Luo WH, Chen AZ. Current situation and development trend of automobile active safety technology and products. Hebei Agric Mach  2015; 12: 45-6.
[37] 
Jeonghoon S. Performance evaluation of a hybrid electric brake system with a sliding mode controller. Chaos Soliton Fract  2005; 15(7): 339-58.
[38] 
Georg FM. A fuzzy logic controller for an ABS braking system. IEEE T Fuzzy Syst  2005; 34(11): 381-8.
[39] 
Mazumdar SK, Lim CC. The application of neural networks to anti-skid brake design. J Neural Networks  2008; 24(5): 109-31.
[40] 
Tanelli M, Osorio G, di Bernardo M, Savaresi SM, Astolfi A. Existence, stability and robustness analysis of limit cycles in anti-lock braking systems. Internet J Contr  2009; 82(4): 659-78.
[http://dx.doi.org/10.1080/00207170802203598] 
[41] 
Sahin M, Unlusoy SY. Design and simulation of an ABS for an integrated active safety for road vehicles. Int J Vehicle Des   2010; 52(1/2/3/4): 64-81.
[42] 
Yu F, Xu ZM, Zhang ZF, He YS. Analysis of fuzzy control and stability simulation of vehicle turning brake ABS. World Sci Tech R&D  2010; 32(6): 782-5.
[43] 
Zhang P, Zhang M, Xia QS, He L. Simulation study of vehicle turning brake anti-lock braking system. Tractor Farm Transp  2009; 36(1): 5-7.
[44] 
Tang BL. Study on the stability control of turning brake and simulation analysis. PhD Dissertation, Northeastern University, Liaoning Province, China, June 2009.
[45] 
Liu ZP. Research on automobile turning brake control strategy. PhD Dissertation, Jilin University, Jilin Province, China, April, 2009.
[46] 
Liu WT. Research on automotive steering brake control strategy. PhD Dissertation, Liaoning University of technology Liaoning Province, China, March, 2017.
[47] 
Yan YB, Wu H, Zhao H. Control of the H∞ robustness of automotive anti-lock braking system. Automot Eng  2014; 36(4): 453-8.
[48] 
Hu XY. EBD control strategy based on ABS hardware system. J Taiyuan Univ  2007; 8(3): 129-30.
[49] 
Nakazawa M, Isobe O, Takahashi S. Braking force distribution control for improving vehicle dynamic characteristics and braking performance. Vehicle Syst Dyn  1995; 24: 413-26.
[50] 
Guo JL. Research on vehicle anti-lock EBD technology. PhD Dissertation, Hebei University of Technology Hebei Province, China, November 2011.
[51] 
Wang H. Simulation of influent factors based on EBD control strategy of vehicle. Automot Technol  2010; 3: 60-3.
[52] 
Wang GY, Zhang L. Electric four-drive vehicle efficient regenerative braking drive integrated system. EBD Composite Control &
China Automotive Engineering Association Academic Annual Conference,
Automotive Engineering Association Academic Wuhan
Province, China, October, 2012. 
[53] 
Qi SQ. The study of mixed braking system and the research on EBD/ABS control. PhD Dissertation, Jilin University, Jilin Province, China, May 2017.
[54] 
Zhang WL. Research on ABS/EBD control strategy based on slip rate. PhD Dissertation, Jilin University, Jilin Province, China, May, 2008.
[55] 
Chen YY, Yang XJ, Zhang K. Research on coordination control of EBD/ABS based on CarSim. Agric Equip Veh Eng  2017; 55(9): 44-8.
[56] 
Zhang LZ. Research on ABS/EBD simulation based on fuzzy control. Jilin University. PhD Dissertation, Jilin Province, China, May, 2009.
[57] 
Li R, Wang R, Zhao S, Xie Y, Yuan W. Classification control and simulation of the power distribution of automobile electronics. J Chongqing Univ Posts Telecommun [Nat Sci Ed  2009; 21(3): 398-401.
[58] 
Serra S, Martinotto L, Donzelli D, Terranova M. Antilock braking systems, devices, and methods using sensorized brake pads. US10227064 2017.
[59] 
Strehle A, Flinner M, Schanzenbach M, Schmidt T. Electronically slip-controllable braking system. US10576953 2020.
[60] 
Tanimoto M. Brake control apparatus for vehicle. US10486665 2018.
[61] 
Edren J, Boecker M, O'Leary RF. Brake force distribution. US10189476 2019.
[62] 
Wou JS, Offerle TG. Systems for distributing braking force and related methods. US10414388 2019.
[63] 
Nam IH. Apparatus and method for failsafe in electric corner module system. US10538163 2019.
[64] 
Zhou YC. Auto brake auxiliary system BAS. Automob Electron  2005; 6: 43-4.
[65] 
Feng J, Wang RX, Sun YD. An auxiliary braking system applied to crawler engineering machinery. Eng Mach  2012; 43(4): 9-11.
[66] 
Continental group launches EBA-City and SPEED products to support safe driving without incident. Automobile Parts  2011; 10: 31-2.
[67] 
Jin LB. Research on the comprehensive performance detection system of the functional vacuum booster of the BA function. PhD Dissertation, China Metrology Institute, Shandong Province, China, March 2013.
[68] 
Zhang HF, Yan SC. Design of real-time automotive electronic assisted braking control system. Modern electronics technology  2016; 39(1): 153-156+162.
[69] 
Svensson T. Method for operating a vehicle braking assist system. US10315630 2019.
[70] 
Nishimura M. Vehicle collision avoidance assist system. US10486692 2019.
[71] 
Lin CG. Electronic four-wheel drive system and its control method. CN106184166 2016.
[72] 
Liao ZJ, Kong DG.  Vehicle aided driving method and vehicle aided driving system. CN106926842 2017.
[73] 
Lou J. Research on the traction control of flexible working face of heavy duty vehicles. Mech Transm  2015; 39(6): 93-7.
[74] 
Jiang LB, Qiu HC, Wu ZW, Liu W, Cheng C. Four-wheel drive vehicle traction control system control strategy. J Beijing Univ Aeronaut Astronaut  2016; 11: 2289-98.
[75] 
Shao LF, Xiang H, Yi BF. Simulation research on the traction system of neuro fuzzy control. Mech Manuf  2014; 52(5): 24-6.
[76] 
Yang C, Song J, Li L, Huang QA, Li HZ. Control of optimal driving torque in traction control system. J Tsinghua Univ [Nat Sci Ed  2008; 11: 1989-92.
[77] 
Li L, Kang MX, Song J, Li HZ, Han ZQ, Yang C. Adaptive PID control of auto traction control system. J Mech Eng  2011; 47(12): 92-8.
[http://dx.doi.org/10.3901/JME.2011.12.092] 
[78] 
Jiang LB, Huang SC, Liu W, Qiu SJ, Ma L. The method of driving traction control ground driving force of the four-wheel drive vehicle based on GIM tires. Mach Tool Hydrau  2014; 44(21): 52-7.
[79] 
Liu G, Ji LQ, Chen PF. The traction control algorithm based on optimal slip ratio in complex working conditions. J Jilin Univ [Eng Ed  2016; 46(5): 1391-8.
[80] 
Ran X, Zhao X. Novel coordinated algorithm for traction control system on split friction and slope road. Int J Automot Technol  2016; 17(5): 817-27.
[http://dx.doi.org/10.1007/s12239-016-0080-3] 
[81] 
Zhou B, Xu M, Yuan XW, Fan L. Vehicle driving anti-slip control strategy based on the sliding mode extreme value search algorithm. T Chin Soc Agric Mach  2015; 46(2): 307-11.
[82] 
Zhang BH, Chen ZM, Fu JH, Chen B. Research on adaptive driving control of electric vehicles driven by four-wheel independent drive. J Shandong Univ [Eng Ed  2017; 6: 1-7.
[83] 
Li ZY, Zhang B, Hou SY, Li HD, Chang YX. Research on the sliding speed of automobile driving anti-skid control system under accelerated conditions. Automot Technol  2009; 7: 23-5.
[84] 
Berels DJ. Traction and stability control system. US10486664 2019.
[85] 
Reed GR. Road surface traction system. US10493966 2019.
[86] 
Zhou ZL, Xu LY. ABS Principle and Structure.  2nd ed. Mechanical Industry Press Beijing, China 2011.
[87] 
Long SX. Automotive ESP control strategy and control based on ESP/ABS integration research. PhD Dissertation, Jilin University, Jilin Province, China, June, 2014.
[88] 
Fu H. Study on the angle estimation and control strategy of automotive electronic stability system. PhD Dissertation, Jilin University, Jilin Province, China, October 2008.
[89] 
Guo JH, Chu L, Liu MH. Automobile ESP fuzzy adaptive control. Automot Technol  2009; 3: 18-22.
[90] 
Gao M, Zhao N, Zhang RY. The development and simulation study of the ESP hardware in the loop based on LabVIEW. Auto Parts  2013; 6: 53-6.
[91] 
Yu HJ, Liu XY, Fang M. Research on the control method of automobile ESP based on ANFIS. J Hefei Univ Technol (Nat Sci Ed)  2010; 33(7): 1015-9.
[92] 
Huo C. Research on automobile ESP fuzzy control strategy based on phase plane analysis. PhD Dissertation, Jilin University, Jilin Province, China, May 2012.
[93] 
Zhao ZQ. Research on automobile ESP control system based on CAN bus. PhD Dissertation, Chang’an University, Shanxi Province, China, May, 2009.
[94] 
Wen JJ. Detailed solutions of active safety VSC system. Driving Park  2009; 1: 56-8.
[95] 
Li J, Zhang J, Yang K, Wang K, Wei Q, Wu ZX. Electronic mechanical braking stability of vehicle Electronic Control Unit (ECU) for control software development and hardware in loop test. J Jilin Univ [Eng Sci  2011; 9(4): 893-7.
[96] 
Zhu DJ, Chen N, Ren ZP. Vehicle stability control based on the theory of H∞ infinity. Precis Manuf Automat  2005; 1: 49-52.
[97] 
Chen WW, Liu XY, Yang J, Huang H. Vehicle stability control hardware in the ring system based on the LabVIEW. China Mech Eng  2010; 21(23): 2882-6.
[98] 
Yuan HJ. Vehicle Dynamic Stability Control (DSC) system. Journal of Chongqing Vocational and Technical College  2006; 5: 146-8.
[99] 
He YC, Li L, Song J, Li HZ, Wu KH. Dynamic stability factor model and analysis of vehicle under extreme conditions. J Automot Saf Energy  2010; 11(4): 320-6.
[100] 
Li L, Jia G, Song J, Ran X. Research progress of automotive dynamic stability control. J Mech Eng  2013; 49(24): 95-107.
[http://dx.doi.org/10.3901/JME.2013.24.095] 
[101] 
Jiang HB, Su J, Zhang HZ. Research on DYC system of electric wheeled vehicles based on the combined sliding mode structure. Automot Technol  2017; 7: 47-53.
[102] 
Yang Y, Qin XF, Xu YK, Nie Y. Research on the control of vehicle side wind stability based on AFS and DYC. J Hunan Univ [Nat Sci Ed  2014; 41(5): 14-9.
[103] 
Ding XY, Wang YN, Tian YK, Shen SY, Wu GL. Simulation of DYC control hardware in electric wheeled vehicles. J Shenyang Univ Technol  2015; 37(4): 440-5.
[104] 
Qiu H, Dong ZR, Lei ZB. The integrated control and test of the four-wheel independent driving electric vehicle ARS and DYC. J Jiangsu Univ [Nat Sci Ed  2016; 37(3): 268-76.
[105] 
Wang WD, Ding NG, Liu H, Li HC. Research on the LQG/LTR robust control method of automobile DYC. J Beijing Univ Technol  2011; 37(3): 353-60.
[106] 
Keighobadi J, Fazeli KA, Shahidi MS. Self-constructing neural network modeling and control of an AGV. Comput Sci Commun  2013; 4(2): 160-8.
[107] 
Keighobadi J, Yarmohammadi MJ. New chatter-free sliding mode synchronization of steer-by-wire systems under chaotic conditions. J Mech Sci Technol  2016; 30: 3829-34.
[http://dx.doi.org/10.1007/s12206-016-0746-9] 
[108] 
Huang H, Zhou TM, Shi GL, Wang QS, Zhao LF. The control of direct horizontal pendulum torque based on the estimation of the lateral stiffness of the automobile. J Hefei Univ Technol (Nat Sci)  2013; 3(6): 660-3.
[109] 
Zong CF, Zheng HY, Tian CW, Pan Z, Dong YL, Yuan DM. The control strategy of automobile stability based on direct transverse pendulum torque. J Jilin Univ (Eng)  2008; 5: 1010-4.
[110] 
Jung JH. Method for side slip angle variable control of vehicle having rear wheel steering system. US10526012 2018.
[111] 
Ramanujam R, Sanford ST, Varunjikar TM, Yang T. Steering system detecting vehicle motion states. US10099720 2017.
[112] 
Carlos CDG, Filho AMM. Integrated chassis control. US10407035 2019.
[113] 
Mahabadi SAK, Litkouhi BB. Methods and systems for vehicle lateral force control. US10266202 2018.
[114] 
Zwicky TD, Elwart S. Hafner, m. Steering and braking control system. US9925988 2018.
[115] 
Katzourakis D, Mees H, Gadda CD. Vehicle stability control system. US10384672 2019.
[116] 
Katsuyama E, Kobayashi T. Vehicle stability control device. US10196057 2019.
[117] 
Oh WJ. Adaptive front steering system for vehicle. US10071760 2018.
[118] 
Mahabadi SAK, Litkouhi BB. Methods and systems for determining a vehicle spin-out condition. US9988043 2018.
[119] 
Wang YQ. Safety control system and method for use in vehicles. US20200039529 2020.

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DOI https://dx.doi.org/10.2174/2212797613999200604155414	Print ISSN 2212-7976
Publisher Name Bentham Science Publisher	Online ISSN 1874-477X

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