Robust vehicle mass and driving resistance estimation

Altmannshofer, Simon; Endisch, Christian

doi:10.1109/acc.2016.7526754

Cited by 20 publications

(10 citation statements)

References 12 publications

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“…Figure 8, we can see that the estimates capture the given actual mass for three different cases. Hence, compared to estimation mechanisms in other existing approaches [1][2][3][4][5][6][7][8][9][10][11][12][13][14][15], it is of tremendous benefit to predict the unknown mass, without perceiving the information of a road grade. Furthermore, Figure 9 shows the estimation results of unloaded truck based on two different actual field test datasets.…”

Section: Vehicle Mass Estimation Using the Characteristics Of Engine mentioning

confidence: 99%

“…Based on perturbation theory, Fathy [5] simplifies the mass estimation model with the differential equation of longitudinal dynamics. A robust parameter algorithm for the vehicle mass and driving resistance estimation has been proposed by [6], and it overcomes the drawbacks of outliers and insufficient excitation. To further improve the accuracy and robustness of the mass estimation, a torque observer was also applied into the system [7].…”

Section: Introductionmentioning

confidence: 99%

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A New Adaptive Mass Estimation Approach of Heavy Truck Based on Engine Torque Local Convex Minimum Characteristic at Low Speeds

Jung

Choi

2020

Energies

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This paper proposes a new mass estimation for a vehicle system, utilizing the characteristics of engine torque local convex minimum, where the mass can be estimated based on the driving forces and the longitudinal accelerations only. Fundamentally, this approach generally requires no other information about an aerodynamic effect, a road grade, or a rolling friction, which is usually demanded by the existing well-known longitudinal dynamics and adaptive filter-based estimation methods. The effectiveness of the proposed approach was evaluated and validated by both TruckSim/Simulink co-simulation and actual field test data. It is found that the proposed estimation technique is more favorable for a situation where the vehicle is exposed to low-speed regions. In addition to this new mass estimation strategy, other new and current existing methods were explored and are reviewed here. Moreover, this study suggested a guideline for a hybrid-type mass estimation strategy to predict a mass by combining a new method with an existing one for every speed.

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Section: Vehicle Mass Estimation Using the Characteristics Of Engine mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A New Adaptive Mass Estimation Approach of Heavy Truck Based on Engine Torque Local Convex Minimum Characteristic at Low Speeds

Jung

Choi

2020

Energies

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“…For the problem of unknown driving resistance in vehicle dynamics, Altmannshofer and Endisch [18] proposed a robust parameter estimation algorithm for identifying the vehicle driving resistance. Tannoury et al [16] designed a nonlinear observer for the estimation of tire radius and rolling resistance to compensate for the unknown parameters.…”

Section: Introductionmentioning

confidence: 99%

Distributed Adaptive Sliding Mode Control for Vehicle Platoon with Uncertain Driving Resistance and Actuator Saturation

Song

2020

Complexity

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Vehicle platoon has been demonstrated to be a promising driving pattern for its prominent advantages in enhancing traffic safety, improving highway capacity, and increasing fuel economy as well as reducing carbon emissions. However, the uncertain driving resistance and saturated actuator output decay the control performance and may even lead to the instability of a vehicle platoon. Therefore, a distributed adaptive sliding mode control algorithm for vehicle platoon with uncertain driving resistance and actuator saturation is proposed in this paper. First of all, sliding mode control technique, together with the coupled sliding surface (CSS) method, is adopted to design the vehicle platoon control algorithm and an adaptive updating law is proposed to estimate the unknown driving resistance coefficients. Then, for the problem of actuator saturation, an antiwindup compensation-based approach is utilized to attenuate the integral windup of the adaptive platoon control laws in the case of actuator saturation. In addition, considering the chattering problem inherent in sliding mode control, a sigmoid-like function sgn⋅ is deployed to weaken the influence of chattering, which is expected to enhance the driving comfortableness. Both theoretical analysis and numerical simulation verify the feasibility and effectiveness of the proposed vehicle platoon algorithm.

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“…The RLS was used to estimate vehicle mass along with system error simultaneously, and qualitative and quantitative analysis of the system error was done. Altmannshofer and Endisch 17 provided a KF combining robust and anti-windup to estimate both vehicle mass and driving resistance, as a result of which, the drawback of outliers was overcome and the lasting excitation was no longer needed. Lei et al 18 used an extended Kalman filter (EKF) to estimate vehicle mass and road grade simultaneously.…”

Section: Introductionmentioning

confidence: 99%

Two-layer structure algorithm for estimation of commercial vehicle mass

Cai

Wang

Jia

et al. 2019

Proceedings of the Institution of Mechanical Engineers, Part D:

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Aiming at the problem of mass estimation for commercial vehicle, a two-layer structure mass estimation algorithm was proposed. The first layer was the grade estimation algorithm based on recursive least squares method and the second layer was a mass estimation algorithm using the extended Kalman filter. The estimated grade was introduced as the observation quantity of the second layer. The influence of the suspension deformation on grade estimation was considered in the first layer algorithm, which was corrected in real time according to the mass and road grade estimated by the second layer algorithm. The proposed estimation algorithm was validated via a co-simulation platform involving TruckSim and MATLAB/Simulink. Finally, a road test was carried out, and the evaluation method using the root mean square error was proposed. According to the test, the average value of the root mean square error reduces from 871.65 to 772.52, grade estimation is more accurate, and the convergence speed of mass estimation is faster, compared with estimation results of the extended Kalman filter method.

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Robust vehicle mass and driving resistance estimation

Cited by 20 publications

References 12 publications

A New Adaptive Mass Estimation Approach of Heavy Truck Based on Engine Torque Local Convex Minimum Characteristic at Low Speeds

A New Adaptive Mass Estimation Approach of Heavy Truck Based on Engine Torque Local Convex Minimum Characteristic at Low Speeds

Distributed Adaptive Sliding Mode Control for Vehicle Platoon with Uncertain Driving Resistance and Actuator Saturation

Two-layer structure algorithm for estimation of commercial vehicle mass

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