Simulation Study on Predictive Cruise Control Strategy for an Electric Heavy Duty Truck

This paper focuses on Predictive Cruise Control (PCC) strategy for a 49t EV heavy duty truck with trailer which is driven by three traction e-Motors. The PCC strategy obtains the road gradient data in preview from navigation, and then calculates the optimal speed to pass through. The goal of PCC str...

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Bibliographic Details
Published in2021 IEEE Sustainable Power and Energy Conference (iSPEC) pp. 3593 - 3597
Main Authors Liu, Qingbo, Wei, Jianlin, Sun, Hao, Lin, Yuanze, Xu, Shengzhong, Liu, Dechun
Format Conference Proceeding
LanguageEnglish
Published IEEE 23.12.2021
Subjects
Energy consumption
EV truck
PCC
predictive cruise control
Predictive models
Roads
Simulation
Software packages
Vehicle driving
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Summary:This paper focuses on Predictive Cruise Control (PCC) strategy for a 49t EV heavy duty truck with trailer which is driven by three traction e-Motors. The PCC strategy obtains the road gradient data in preview from navigation, and then calculates the optimal speed to pass through. The goal of PCC strategy is to reduce vehicle energy consumption while the vehicle driving on the road with varied gradients. There are two main functions developed for the PCC strategy, which is the road preview segmentation function, and the speed planner function, among speed planner there are cost calculation and optimization function. The developed strategy is evaluated in simulation based on a combined TruckMaker / Matlab Simulink vehicle/ powertrain plant model. The PCC energy consumption benefits are demonstrated by the comparison to a simulated standard driver in TruckMaker using constant cruise speed on the route, while the PCC changes vehicle speed predictively according to the road gradient conditions within a speed band. The simulation investigation shows that, by applying the PCC strategy could lead a 3% energy save under predictive cruise control with full load condition.
DOI:10.1109/iSPEC53008.2021.9735738