Collaborative optimization and energy management of hydraulic hybrid mining trucks

This article discusses the fuel economy optimization of a parallel hydraulic hybrid mining truck (HHMT). Considering the influences of various coupled factors, such as the transmission system, energy management strategy, and driving conditions, on the optimization goal, this article proposes the use of a double-layer optimization strategy with a collaborative optimization algorithm that combines particle swarm optimization (PSO) and a dynamic programming algorithm (DP) to eliminate the mutual effects of these coupled factors. A two-layer optimization model is developed, with powertrain parameters and energy management parameters as the optimization variables and the average fuel consumption under various driving conditions as the target. This model combines a variety of driving conditions to perform global optimization of the transmission system parameters while calculating the optimal energy distribution and analyzing the influences of various factors on the optimization goal. To achieve real-time and reliable control of energy management, the optimal energy management strategy rules obtained under various driving conditions are integrated and extracted, and an improved extraction method compared with the traditional extraction method is proposed. Finally, a rule-based energy management strategy is established. The strategy and optimized transmission system parameters are simulated and verified using a MATLAB and AMESIM joint simulation platform, and the effect of the rule strategy is evaluated. The obtained fuel consumption results are close to the results obtained by PSO-DP optimization, and the strategy is robust. The experiment verifies the effectiveness, feasibility and reliability of the optimization scheme, and extraction rule control strategy.

Online optimization of Pontryagin’s minimum principle for a series hydraulic hybrid wheel loader

The hydraulic hybrid powertrain has great potential for reducing fuel consumption and emission of off-road vehicles. The energy management strategy is the key to hybrid powertrain and currently there are many well-developed strategies. Of which the Pontryagin’s minimum principle is of research interest since it is a global optimization method while less computational burden than dynamic programming. However, it requires full cycle information to calculate co-state value in the principle, making it not implementable. Therefore in this study an implementable Pontryagin’s minimum principle is proposed for a series hybrid wheel loader, where the optimal co-state value in the principle is trained through repetitive wheel loader duty cycle. The Pontryagin’s minimum principle formulations of hybrid wheel loader are developed. The online co-state training algorithm is presented. A dynamic simulation model of hybrid wheel loader is developed. The fuel consumption of hybrid wheel loader with proposed strategy is compared with dynamic programming strategy and rule-based strategy in wheel loader long and short loading cycles. Results show the fuel consumption with proposed strategy is close to dynamic programming result and is lower than rule-based strategy. Finally, the influence of pressure level of hybrid powertrain on vehicle fuel consumption is studied.

Parameter Matching of Energy Regeneration System for Parallel Hydraulic Hybrid Loader

Oil shortages and environmental pollution are attracting worldwide attention incrementally. Hybrid falls within one of the effective techniques for those two problems. Taking the loader with high energy consumption and high emission as the target, combined with the hydraulic hybrid technology with high power density and strong energy storage capacity, the parallel hydraulic hybrid loader (PHHL) based on brake energy regeneration is proposed. Firstly, the dynamic models of the key components of the PHHL are established, and the parameters of the part which coincides with the ordinary loader are corrected based on the V-type duty cycle. Then, consid-ering the energy recovery efficiency as well as the characteristics of the loader from the V-type duty cycle, the parameters for several major parts of the energy regeneration system (ERS) were calculated and matched. Then, based on the initial matching, the improved adaptive genetic al-gorithm (AGA) is employed to optimize the control variable of the control strategy and the design parameters of ERS to enhance the economic benefit and performance of the ERS. Furthermore, a simulation validation was conducted. Simulation results show that the ERS with optimized pa-rameters could improve the fuel-saving effect by 25% compared to the ERS with initial parameters, which indicated the rationality of the optimized parameters. Finally, the fuel consumption test of the PHHL prototype under the V-type duty cycle is performed. The results show that the PHHL with the optimization scheme can achieve 9.12% fuel saving, which is on the brink of the potential of brake energy recovery and verifies the feasibility of applying hydraulic hybrid technology on the loader.

Modelling and experimental validation of the performance of a digital displacement® hydraulic hybrid truck

The development, modelling and testing of a novel, fuel-efficient hydraulic hybrid light truck is reported. The vehicle used a Digital Displacement® pump/motor and a foam-filled hydraulic accumulator in parallel with the existing drivetrain to recover energy from vehicle braking and use this during acceleration. The pump/motor was also used to reduce gear-shift times. The paper describes the development of a mathematical vehicle model and the validation of this model against an extensive testing regime. In testing, the system improved the fuel economy of the vehicle by 23.5% over the JE05 midtown drive cycle. The validated mathematical model was then optimised and used to determine the maximum fuel economy improvement over the diesel baseline vehicle for two representative cycles (JE05 midtown and WLTP). It was found that the hybrid system can improve the fuel economy by 24%–43%, depending on the drive cycle. When this was combined with engine stop-start, the system improved the fuel economy of the vehicle by 29%–95%, depending on the drive cycle.

Technical Solutions of Forest Machine Hybridization

The paper deals with the characteristics of three different types of power train hybridization of forest logging machines and with the benefits of reducing environmental impacts by comparing new technology with more conventional, older technology. New hybridization options that could be implemented in forestry machines are also discussed. The paper divides a hybrid solution into three classes based on the energy used in the system of hybridization. First is an electro-hybrid system that uses an electric motor and battery or different storage device. The second, a hydraulic hybrid system, is a solution with a hydraulic accumulator, hydraulic motor, and pump. The third system is a combination of the electro-hybrid and hydraulic-hybrid system. The current technical and technological development of hybrid drive systems, as well as their components, has led to significant improvements in drive performance and thus better performance of the new generation of forest vehicles. Improved energy efficiency using hybrid propulsion systems in forest vehicles would result in a significant reduction in greenhouse gas emissions and possibly lower maintenance costs.