Modeling and control of heat pump system for battery electric buses

Given the continuous tightening of emissions regulations on vehicles, battery-electric buses (BEB) play an essential role in the transition toward cleaner transport technologies, as they represent the most promising solution to replace diesel buses and reduce their environmental impact in the short term. However, heating the bus cabin leads to a considerable increase in energy consumption under cold weather conditions, which significantly reduces the driving range, given the limited battery capacity. Heat pumps (HP) are the primary heating technology used in BEB for their improved consumption performance compared to other technologies. Therefore, this study aims at optimizing the coefficient of performance (COP) of an HP system in a BEB for maximizing the bus electric driving range under cold weather conditions while maintaining satisfactory thermal comfort levels for passengers. Accordingly, an HP model is developed and integrated into an electric bus model using Dymola. A genetic algorithm (GA) based controller is proposed to find the optimal combination of the HP operating parameters, namely the compressor speed, the air mass flow rate at the inlet of the condenser, and the recirculation rate in order to maximize the system’s COP, and extend the BEB driving at different external temperatures, and as a function of the passengers’ occupancy levels. Results are carried under transient and steady-state operating conditions and show that the proposed GA-based controller saves up to 39% of the HP energy consumption as compared to the conventional HP control strategy, and therefore, enhances the BEB driving range up to 17%.

The Impact of HVAC on the Development of Autonomous and Electric Vehicle Concepts

Automation and electrification are changing vehicles and mobility. Whereas electrification is mainly changing the powertrain, automation enables the rethinking of the vehicle and its applications. The actual driving range is an important requirement for the design of automated and electric vehicles, especially if they are part of a fleet. To size the battery accordingly, not only the consumption of the powertrain has to be estimated, but also that of the auxiliary users. Heating Ventilation and Air Conditioning (HVAC) is one of the biggest auxiliary consumers. Thus, a variable HVAC model for vehicles with electric powertrain was developed to estimate the consumption depending on vehicle size and weather scenario. After integrating the model into a tool for autonomous and electric vehicle concept development, various vehicle concepts were simulated in different weather scenarios and driving cycles with the HVAC consumption considered for battery sizing. The results indicate that the battery must be resized significantly depending on the weather scenario to achieve the same driving ranges. Furthermore, the percentage of HVAC consumption is in some cases higher than that of the powertrain for urban driving cycles, due to lower average speeds. Thus, the HVAC and its energy demand should especially be considered in the development of autonomous and electric vehicles that are primarily used in cities.

Comparison of TrackMan Data between Professional and Amateur Golfers at Swinging to Uphill and Downhill Fairways

Background: Golfers face different environmental conditions in each game played under various constraints. Enhancing affordances through training in a constrained outdoor environment is crucial. Objective: To analyze club head behavior at ball impact of a tee shot by 42 professional (PGs) and 25 amateur (AGs) golfers in swinging to uphill and downhill fairway environments using the TrackMan portable launch monitor. Methods: We used TrackMan to compare golf club movement adaptations in 42 PGs and 25 AGs. A 330-m driving range facing both the uphill (+5°) and downhill (-5°) fairways were used. The tee shot area was the only flat ground surface, with the uneven ground between the shot area and the 200-yard fairway. Results: The clubhead speed and attack angle were significantly higher among PGs than among AGs. PGs could adapt their swings to the uphill fairway by increasing the attack angle (3.6°±2.4) by 3.3° compared with the downhill fairway. The attack angle did not correlate with the launch angle among the AGs in the downhill condition, suggesting that they were unable to control the height of the ball based on the far side of the fairway. Conclusion: PGs increased the attack angle in uphill conditions, and their awareness of the affordance, which was different from that of AGs, allowed them to change the optimal ball trajectory to avoid perceived fairway risks. Thus, the more skill a player had, the better he was at recognizing the affordance of the visual field. PGs demonstrated a better ability to adapt to environmental constraints.

Torque Vectoring Control of RWID Electric Vehicle for Reducing Driving-Wheel Slippage Energy Dissipation in Cornering

The anxiety of driving range and inconvenience of battery recharging has placed high requirements on the energy efficiency of electric vehicles. To reduce driving-wheel slip energy consumption while cornering, a torque vectoring control strategy for a rear-wheel independent-drive (RWID) electric vehicle is proposed. First, the longitudinal linear stiffness of each driving wheel is estimated by using the approach of recursive least squares. Then, an initial differential torque is calculated for reducing their overall tire slippage energy dissipation. However, before the differential torque is applied to the two side of driving wheels, an acceleration slip regulation (ASR) is introduced into the overall control strategy to avoid entering into the tire adhesion saturation region resulting in excessive slip. Finally, the simulations of typical manoeuvring conditions are performed to verify the veracity of the estimated tire longitudinal linear stiffness and effectiveness of the torque vectoring control strategy. As a result, the proposed torque vectoring control leads to the largest reduction of around 17% slip power consumption for the situations carried out above.

Analysis and Improvement Measures of Driving Range Attenuation of Electric Vehicles in Winter

A great many EVs in cold areas suffer from range attenuation in winter, which causes driver anxiety concerning the driving range, representing a hot topic. Many researchers have analyzed the reasons for range attenuation but the coupling mechanism of the battery as well as the vehicle and driving conditions have not been clearly estimated. To quantitatively investigate the driving range attenuation of electric vehicles (EVs) during winter, an EV model mainly integrated with a passenger-cabin thermal model, battery model, and vehicle dynamic model was constructed and simulated based on the mass-produced Wuling HongGuang Mini EV. Real vehicle dynamic driving data was used to validate the model. Based on NEDC driving conditions, the driving range calculation formula and energy flow diagram analysis method were used. The reason for attenuation was evaluated quantitatively. Results show that battery energy loss and breaking recovery energy loss contribute nearly half of the range attenuation, which may be alleviated by battery preheating. Suggestions for extending driving range are proposed based on the research.