With the wide application of electric heavy trucks in the field of urban logistics and transportation, the problems of low energy recovery rate and poor braking sensation are becoming more and more prominent. For this reason, this paper proposes a multi-objective optimization research method based on IVY algorithm for electric heavy truck composite braking system. Firstly, according to the characteristics of the electric heavy truck composite braking system, the energy flow process of the composite braking system is analyzed, and the pneumatic brake and motor regenerative braking models are constructed. Secondly, the comprehensive evaluation model of system performance was established by taking braking sensation, energy recovery and loss as the performance evaluation indexes, and the key static parameters affecting the performance of the composite braking system and their influence laws were clarified. Finally, the Ivy algorithm IVYA is used for parameter optimization, and the optimization results are compared and analyzed with the optimization results based on the adaptive genetic particle swarm hybrid algorithm PSO-GA. The optimization results show that the optimized system parameters based on the Ivy algorithm can reduce the loss by 13.9% and increase the energy recovery rate by 20% while ensuring good braking sensation for the driver.