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Center of Gravity Position Estimation of Counterbalanced Forklift Truck Based on Multi Model Data Fusion

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Abstract

The center of gravity of a forklift truck, a crucial parameter for vehicle stability, changes with different loads during operation. We propose an estimation algorithm for the center of gravity position suitable for a counterbalanced forklift truck. By installing sensors on the fork, we use an inclinable platform and propose a static joint center of gravity measurement method. For straight-line driving, we establish a longitudinal dynamics model and propose a nonlinear H∞ estimation algorithm. For steering conditions, we establish a roll dynamics model and propose a forgetting factor recursive least square estimation algorithm. A data fusion algorithm for the forklift truck’s center of gravity position under various working conditions is proposed. The fusion of these estimation results yields the best estimated center of gravity height. We validate the algorithm’s effectiveness using a hardware-in-the-loop simulation platform under different working conditions. The experiments demonstrate the algorithm’s fast parameter fitting, wide applicability, and accurate position control within a 5 % error range.

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References

  • Berntorp, K., Chakrabarty, A. and Di Cairano, S. (2021a). Vehicle center-of-gravity height and dynamics estimation with uncertainty quantification by marginalized particle filter. American Control Conf. (ACC), New Orleans, Louisiana, USA.

  • Berntorp, K., Chakrabarty, A. and Di Cairano, S. (2021b). Vehicle rollover avoidance by parameter-adaptive reference governor. 60th IEEE Conf. Decision and Control (CDC), Austin, Texas, USA.

  • Boada, B. L., Garcia-Pozuelo, D., Boada, M. J. L. and Diaz, V. (2016). A constrained dual Kalman filter based on pdf truncation for estimation of vehicle parameters and road bank angle: Analysis and experimental validation. IEEE Trans. Intelligent Transportation Systems 18, 4, 1006–1016.

    Article  Google Scholar 

  • Fan, X. and Zhang, M. (2020). A new method for static measurement of two axles vehicle centroid height. Recent Patents on Engineering 14, 4, 629–635.

    Article  Google Scholar 

  • Gong, X., Suh, J. and Lin, C. (2020). A novel method for identifying inertial parameters of electric vehicles based on the dual H infinity filter. Vehicle System Dynamics 58, 1, 28–48.

    Article  Google Scholar 

  • Guang, X., Ke, D., Hai, X., Xiwen, T. and Wuwei, C. (2020). Variable universe fuzzy control for the lateral stability of forklift based on the roll classification. J. Mechanical Engineering 55, 12, 157–167.

    Article  Google Scholar 

  • Hong, S., Lee, C., Borrelli, F. and Hedrick, J. K. (2014). A novel approach for vehicle inertial parameter identification using a dual Kalman filter. IEEE Trans. Intelligent Transportation Systems 16, 1, 151–161.

    Article  Google Scholar 

  • Huang, X. and Wang, J. (2013). Center of gravity height real-time estimation for lightweight vehicles using tire instant effective radius. Control Engineering Practice 21, 4, 370–380.

    Article  Google Scholar 

  • Huang, X. and Wang, J. (2014). Real-time estimation of center of gravity position for lightweight vehicles using combined AKF-EKF method. IEEE Trans. Vehicular Technology 63, 9, 4221–4231.

    Article  Google Scholar 

  • Jeong, D., Kim, S., Lee, J., Choi, S. B., Kim, M. and Lee, H. (2021). Estimation of tire load and vehicle parameters using intelligent tires combined with vehicle dynamics. IEEE Trans. Instrumentation and Measurement, 70, 1–12.

    Article  Google Scholar 

  • Jie, Z. (2022). Industrial vehicle industry: Dales volume hit another high record. Logistics Technology and Application 27, 4, 66–69.

    Google Scholar 

  • Kasahara, M. and Mori, Y. (2017). Relation between overturn and the center of gravity of a forklift truck. 56th Annual Conf. Society of Instrument and Control Engineers of Japan (SICE), Kanazawa, Japan.

  • Larish, C., Piyabongkarn, D., Tsourapas, V. and Rajamani, R. (2013). A new predictive lateral load transfer ratio for rollover prevention systems. IEEE Trans. Vehicular Technology 62, 7, 2928–2936.

    Article  Google Scholar 

  • Lee, J., Hyun, D., Han, K. and Choi, S. (2018). Real-time longitudinal location estimation of vehicle center of gravity. Int. J. Automotive Technology 19, 4, 651–658.

    Article  Google Scholar 

  • Li, H. and Shi, Y. (2012). Robust H∞ filtering for nonlinear stochastic systems with uncertainties and Markov delays. Automatica 48, 1, 159–166.

    Article  MathSciNet  MATH  Google Scholar 

  • Lin, C., Cheng, X., Zhang, H. and Gong, X. (2016). Estimation of center of gravity position for distributed driving electric vehicles based on combined H∞-EKF method. Energy Procedia, 88, 970–977.

    Article  Google Scholar 

  • Lin, C., Gong, X., Xiong, R. and Cheng, X. (2017). A novel H∞ and EKF joint estimation method for determining the center of gravity position of electric vehicles. Applied Energy, 194, 609–616.

    Article  Google Scholar 

  • Park, G. and Choi, S. B. (2021). An integrated observer for real-time estimation of vehicle center of gravity height. IEEE Trans. Intelligent Transportation Systems 22, 9, 5660–5671.

    Article  Google Scholar 

  • Patel, S. G. and Topiwala, J. J. (2017). Measuring a centre of gravity of an object using 4 load transducer method. Int. J. Engineering Research and Technology 6, 1, 210–214.

    Google Scholar 

  • Phanomchoeng, G. and Rajamani, R. (2012). New rollover index for the detection of tripped and untripped rollovers. IEEE Trans. Industrial Electronics 60, 10, 4726–4736.

    Article  Google Scholar 

  • Piyabongkarn, D., Rajamani, R., Grogg, J. A. and Lew, J. Y. (2008). Development and experimental evaluation of a slip angle estimator for vehicle stability control. IEEE Trans. Control Systems Technology 17, 1, 78–88.

    Article  Google Scholar 

  • Qin, Z., Chen, L., Hu, M. and Chen, X. (2022). A lateral and longitudinal dynamics control framework of autonomous vehicles based on multi-parameter joint estimation. IEEE Trans, Vehicular Technology 71, 6, 5837–5852.

    Article  Google Scholar 

  • Rajamani, R., Piyabongkarn, D., Tsourapas, V. and Lew, J. Y. (2011). Parameter and state estimation in vehicle roll dynamics. IEEE Trans. Intelligent Transportation Systems 12, 4, 1558–1567.

    Article  Google Scholar 

  • Rozyn, M. and Zhang, N. (2010). A method for estimation of vehicle inertial parameters. Vehicle System Dynamics 48, 5, 547–565.

    Article  Google Scholar 

  • Solmaz, S., Akar, M., Shorten, R. and Kalkkuhl, J. (2008). Real-time multiple-model estimation of centre of gravity position in automotive vehicles. Vehicle System Dynamics 46, 9, 763–788.

    Article  Google Scholar 

  • Stone, E. and Cebon, D. (2010). Control of semi-active anti-roll systems on heavy vehicles. Vehicle System Dynamics 48, 10, 1215–1243.

    Article  Google Scholar 

  • Sun, Y., Li, L., Yan, B., Yang, C. and Tang, G. (2016). A hybrid algorithm combining EKF and RLS in synchronous estimation of road grade and vehicle’ mass for a hybrid electric bus. Mechanical Systems and Signal Processing, 68, 416–430.

    Article  Google Scholar 

  • Wang, C., Wang, Z., Zhang, L., Cao, D. and Dorrell, D. G. (2020). A vehicle rollover evaluation system based on enabling state and parameter estimation. IEEE Trans. Industrial Informatics 17, 6, 4003–4013.

    Article  Google Scholar 

  • Yang, L. (2015). Research on Technologies of the Vehicle Centroid Measurement Platform Based on the Tilting Method. Ph. D. Dissertation. Harbin Institute of Technology. Harbin, China.

    Google Scholar 

  • Yang, X., Wu, C., He, Y., Lu, X. Y. and Chen, T. (2022). A dynamic rollover prediction index of heavy-duty vehicles with a real-time parameter estimation algorithm using NLMS method. IEEE Trans. Vehicular Technology 71, 3, 2734–2748.

    Article  Google Scholar 

  • Yoon, J., Kim, D. and Yi, K. (2007). Design of a rollover index-based vehicle stability control scheme. Vehicle System Dynamics 45, 5, 459–475.

    Article  Google Scholar 

  • Yue, H., Zhang, L., Shan, H., Liu, H. and Liu, Y. (2015). Estimation of the vehicle’s centre of gravity based on a braking model. Vehicle System Dynamics 53, 10, 1520–1533.

    Article  Google Scholar 

  • Zhang, J., Chu, Y., Wang, Z., Ye, T., Cai, L. and Yang, H. (2021). Vehicle pose estimation system base on pressure sensor array for clamping parking robot. IEEE Int. Conf. Mechatronics and Automation (ICMA), Kagawa, Japan.

  • Zhang, L., Qiao, W., Sun, Z. and He, S. (2018). Research on the position of gravity center of telescopic boom forklift based on stability analysis. Hoisting and Conveying Machinery, 1, 80–85.

    Google Scholar 

  • Zhao, H., Chen, W., Zhou, S. and Liu, Y. H. (2021). Parameter estimation of an industrial car-like tractor. IEEE Robotics and Automation Letters 6, 3, 4480–4487.

    Article  Google Scholar 

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Acknowledgement

This study was supported by the National Natural Science Foundation of China (No. 52275100). The authors would like to thank the state funding and all the participants for their assistance.

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Authors and Affiliations

  1. Key Laboratory for Automated Vehicle Safety Technology of Anhui Province, Hefei University of Technology, Hefei, 230009, China

    Guang Xia

  2. School of Automotive and Traffic Engineering, Hefei University of Technology, Hefei, 23009, China

    Guang Xia, Chenhao Zhang, Yang Zhang & Linfeng Zhao

  3. Institute of Radar Confrontation, National University of Defense Technology, Hefei, 230009, China

    Xiwen Tang

Authors
  1. Guang Xia
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  2. Chenhao Zhang
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  3. Xiwen Tang
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  4. Yang Zhang
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  5. Linfeng Zhao
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Correspondence to Guang Xia.

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Xia, G., Zhang, C., Tang, X. et al. Center of Gravity Position Estimation of Counterbalanced Forklift Truck Based on Multi Model Data Fusion. Int.J Automot. Technol. 24, 1335–1347 (2023). https://doi.org/10.1007/s12239-023-0108-4

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  • DOI: https://doi.org/10.1007/s12239-023-0108-4

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