This study presents the development and integration of a vehicle mass estimator
into the ZF’s Adaptive Cruise Control (ACC) system. The aim is to improve the
accuracy of the ACC system’s torque control for achieving desired speed and
acceleration. Accurate mass estimation is critical for optimal control
performance, particularly in commercial vehicles with variable loads. The
incorporation of such mass estimation algorithm into the ACC system leads to
significant reductions in the error between requested and measured acceleration
during both flat and uphill driving conditions, with or without a preceding
vehicle. The article details the estimator’s development, integration, and
validation through comprehensive experimental testing. An electric front-wheel
drive van was used. The vehicle’s longitudinal dynamics were modeled using
D’Alembert’s principle to develop the mass estimation algorithm. This algorithm
updates the mass estimate based on specific conditions: zero brake torque, high
longitudinal acceleration, minimal slope, adequate speed, minimal wheel slip,
and low yaw rate. These conditions ensure accurate mass estimation by minimizing
the effects of nonlinearities and external disturbances. Experimental results
showed that the mass estimator converges to the actual mass value as more
samples are collected. Tests with varying loads confirmed the estimator’s
accuracy, achieving a maximum absolute error of 72 kg and a percentage error of
1.71 %. When integrated into the ACC system, the estimated mass improved the
control accuracy, especially in acceleration phases, reducing the time to reach
the desired speed. Both cruise control and follow control tests, performed on
flat and uphill roads, demonstrated that the ACC system with the mass estimator
achieved the desired acceleration more accurately than without it. This improved
the overall responsiveness and comfort of the ACC system under different driving
conditions. The findings highlight the importance of accurate mass estimation
for enhancing adaptive vehicle control technologies, representing a significant
advancement in ACC systems.
