An Innovative Methodology to Take into Account Traffic Information on WLTP Cycle for Hybrid Vehicles

Abstract

The most efficient energy management strategies for hybrid vehicles are the “Optimization-Based Strategies”. These strategies require a preliminary knowledge of the driving cycle, which is not easy to predict. This paper aims to combine Worldwide Harmonized Light-Duty Vehicles Test Cycle (WLTC) low section short trips with real traffic levels for vehicle energy and fuel consumption prediction. Future research can focus on implementing a new strategy for Hybrid Electric Vehicle (HEV) energy optimization, taking into account WLTC and Google Maps traffic levels. First of all, eight characteristic parameters are extracted from real speed profiles, driven in urban road sections in the city of Messina at different traffic conditions, and WLTC short trips as well. The minimum distance algorithm is used to compare the parameters and assign the three traffic levels (heavy, average, and low traffic level) to the WLTC short trips. In this way, for each route assigned from Google maps, vehicle’s energy and fuel consumption are estimated using WLTC short trips remodulated with distances and traffic levels. Moreover, a vehicle numerical model was implemented and used to test the accuracy of fuel consumption and energy prediction for the proposed methodology. The results are promising since the average of the percentage errors’ absolute value between the experimental driving cycles and forecast ones is 3.89% for fuel consumption, increasing to 6.80% for energy.

Reputation-Based Blockchain for Spatial Crowdsourcing in Vehicular Networks

“…When (n + 1)-th mining round starts, the minimum criterion for joining the mining is the entry threshold h (i) (i ∈ L) for the pool i, and we have h = h (1) , h (2) , . .…”

“…EVs are integrated with many embedded devices, the use of which requires huge parallel data processing and communication capabilities. Researchers and stakeholders have proposed a crowdsourcingaided EVs serving scheme, i.e., vehicle users involved in large-scale perception [2,3]. As increasingly multifunctional services need to make full use of the dynamic information of EVs, the crowdsourcing framework can help achieve coordination and unity between the application layer, network layer, and collection layer.…”

“…The security and high efficiency of blockchain technology mainly depends on the participation of a large scale of nodes, that is, more miners involved in blockchain will provide better system performance concerning security and efficiency. However, there are still some limitations that need to be solved urgently: (1) The blockchain nodes lack motivation to become involved in the blockchain, especially weak-computational ability nodes; (2) Although the blockchain nodes are mostly low-power devices, redundant computational resources are still present; (3) The blockchain ensures that damage to system security can occur only when the computational capability reaches more than 51%; however, it cannot supervise and guarantee the honest behavior of nodes. Hence, the current research focus aims at the design of a credible blockchain incentive mechanism based on a reputation framework, so that the vehicle-crowdsourcing platform can achieve credible and reasonable resource allocation.…”

Smart Design: Application of an Automatic New Methodology for the Energy Assessment and Redesign of Hybrid Electric Vehicle Mechanical Components

“…Finally, the vehicle speed is matched with a reference speed (drive cycle) through a control system acting on the throttle/brake pedal position. In addition to the mathematical modelling, the increasing usage of machine learning and neural network algorithms [25][26][27][28][29] has led to new vehicle control and design strategies [30]. An important aspect to investigate is the stress state acting on the mechanical components when the vehicle is hybridized, starting from a conventional configuration i.e., only with the ICE engine propulsion.…”

Influence of Energy Management System Control Strategies on the Battery State of Health in Hybrid Electric Vehicles

“…These management algorithms generally include a fully electric driving and a fully thermal driving mode, and other hybrid modes. In hybrid modes, the thermal engine may have the task of supporting traction, and at the same time recharging the battery, or simply a marginal role in the traction or operating at predefined working points [13][14][15][16][17].…”