Optimal Sizing and Control Strategy Design for Heavy Hybrid Electric Truck

Abstract

Due to the complexity of the hybrid powertrain, the control is highly involved to improve the collaborations of the different components. For the specific powertrain, the components' sizing just gives the possibility to propel the vehicle and the control will realize the function of the propulsion. Definitely the components' sizing also gives the constraints to the control design, which cause a close coupling between the sizing and control strategy design. This paper presents a parametric study focused on sizing of the powertrain components and optimization of the power split between the engine and electric motor for minimizing the fuel consumption. A framework is put forward to accomplish the optimal sizing and control design for a heavy parallel pre-AMT hybrid truck under the natural driving schedule. The iterative plant-controller combined optimization methodology is adopted to optimize the key parameters of the plant and control strategy simultaneously. A scalable powertrain model based on a bilevel optimization framework is built. Dynamic programming is applied to find the optimal control in the inner loop with a prescribed cycle. The parameters are optimized in the outer loop. The results are analysed and the optimal sizing and control strategy are achieved simultaneously.

Urban and Extra-Urban Hybrid Vehicles: A Technological Review

“…This "oversizing" has, inevitably, an impact on the installation, operation and maintenance costs. [19,20]. Regarding the vehicles' specific issues, two braking torque control strategies for the parallel power trains of hybrid duty trucks have been introduced [21].…”

Challenges of micro/mild hybridisation for construction machinery and applicability in UK

“…The basic concept of a OPT controller is to utilize the knowledge of future and past power demands to minimize a cost function of fuel consumption, and/or emissions, and/or time/distance travelled over a fixed driving cycle. Well-known global optimization approaches can be counted as model-based control [54], RB optimal control [54][55][56], optimal control [57], DP-based optimization [58,59], and GA-based optimization [60]. Meanwhile, real-time optimization approaches are recognised as equivalent fuel consumption minimization [61], robust control [62], and real-time predictive optimization [63].…”

Optimizing Gear Shifting Strategy for Off-Road Vehicle with Dynamic Programming

“…With known road data, it is available to use dynamic programming approach to optimize the gear shifting strategy to reduce the fuel consumption and trip time. As a numerical method for solving multistage decision-making problems, dynamic programming has been applied to optimize fuel and electricity costs associated with two supervisory control strategies for a series of plug-in hybrid electric vehicle and control strategy for heavy hybrid electric truck [2,3]. Besides, it is proposed for design of the optimal gear shift strategy to study quantitatively an optimal trade-off between the fuel economy and the drivability [4].…”