Does travelling at high speeds thrill you? Do you like overtaking vehicles travelling faster than you? Read on to know about how this driving style affects your day-to-day EV range apart from your reputation with the traffic police.
In our previous blog, we saw the 3 main factors that affect the range of an EV battery.
- Man
- Machine
- Environment
In this article, we discuss factors that a man (user) has control over which affect the range of an EV.
One of the most well-known enemies of electric vehicles in India and their marketing is: “Range Anxiety”. It is the phobia that an EV user would run out of charge before they reach their destination. Why is the range in an EV so critically examined? This is linked to the energy density of the EV battery.
Energy density is simply defined as the amount of energy stored in a given mass or volume. There are two types of energy density in EV’s with a specified battery pack.
They are energy per unit mass and energy per unit volume. These two types of energy densities indicate the weight of the battery and the amount of space it occupies in the EV given its energy rating.
While comparing Li-ion batteries and fossil fuels the energy density is much lesser in batteries. This leads to “Range Anxiety” in EV users. The range of any vehicle is decided by its fuel’s amount of stored energy and the rate at which this energy is depleted during usage. An electric vehicle’s battery decides the range. The range may be influenced by various factors that may or may not be in a user’s control. Thus, to maximize range we need to know how these factors affect our range.
In this blog, we will be writing about all the parameters that affect the EV range that is under the user’s control. These include the following:
- Acceleration & Braking
- Travelling at High Speeds
- Usage of Regenerative Braking
Generally, harsher accelerations, harsher brakings and higher speeds decrease the range. And usage of the regenerative braking present in EVs increases the range.
- Acceleration and Deceleration
Harsh accelerations reduce the state of charge (SOC) faster than smoother accelerations. These attributes to several energy losses which occur during harsh acceleration such as:
Frictional losses In electric vehicles the battery’s current power the wheels. During harsh accelerations, electric motors provide larger torques to the shaft and gears. This causes high frictional losses in the gears as heat (which is a waste).
Thermal Losses Under harsh accelerations, the battery has to supply additional energy to the motor. It sends larger currents to achieve the desired speed within a short period of time. Thermal losses occur when motor windings are exposed to these large currents for a long period of time.
During harsh brakings, the battery does not consume energy. But, the brake pads apply a frictional force to the wheels to halt them. This contributes to an indirect waste of charge.
2. High Speed
Air resistance negatively impacts the energy consumption of all vehicles including EVs. But it is most prevalent at high speed.
At all speeds there exists a frictionally induced rolling resistance. It exists between the tyres and road generating wasted energy as heat. This resistance adds to the air resistance depleting more energy. The Department of Energy states that a decrease of 15 km/h in the speed used in an EV can decrease energy consumption by more than 14%.
3. Regenerative Braking
In electric vehicles, OEMs have created a mechanism where-in the motor will automatically generate reverse torque from a free-spinning wheel. This mechanism charges the battery by a small amount. This is regenerative braking.
With every regenerative braking, the range increases every time. Thus, regenerative braking presents an opportunity to increase the state of charge (SOC). For example, when one travels down the hill in an electric scooter, the state of charge increases.
Generally, the most efficient way to drive the EV is to adopt a smooth driving style. This involves utilizing regenerative braking effectively.
Nesh connectivity solutions for EV manufacturers retrieves and analyzes the battery and vehicle data discussed above to predict the battery’s state of health (SOH) and state of charge (SOC) at a given time. This allows the prediction of range and timely notifications to the user. Additionally, we can also provide alert messages to the user if needed, upon harsh braking, accelerations and over-speeding. Such continuous monitoring of performance helps manufacturers to drive safety and efficiency of their vehicles along with a seamless customer experience.
